Risk avoidance scheduling method and system for geographically distributed energy alliance

Abstract

The invention belongs to the technical field of renewable energy source grid connection, and discloses a risk avoidance scheduling method and system for a geographically distributed energy alliance, and the method comprises the steps: building an energy alliance self-balancing scheduling certainty model with maximization of internal benefits as a target through obtaining equipment parameters, meteorological parameters, load parameters and economic parameters; the energy alliance self-balancing scheduling deterministic model can provide an accurate deterministic solution under a predicted value parameter based on actual data, so as to effectively guide energy scheduling; the risk scheduling model established in combination with the information gap decision theory can deal 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. By adopting the scheduling method, the economical efficiency and the robustness of the energy alliance facing the transmission blocking risk are remarkably enhanced, and a scientific and effective solution is provided for energy management of a third-party entity.

Description

Technical Field

[0001] The present invention belongs to the technical field of renewable energy grid connection, and in particular relates to a risk avoidance scheduling method and system for a geographical distributed energy alliance. Background Art

[0002] Wind and solar energy are intermittent, volatile and random. The reliable and efficient operation of power systems with a high proportion of new energy is facing huge 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 technologies, using flexible loads to provide regulation services and demand response for power systems is a promising approach. By reaching a medium- and long-term agreement, geographically distributed new energy power generation systems, flexible loads based on distributed energy systems, and large electricity users can form an energy alliance. Under direct load control, the flexible loads on the demand side play their flexible regulatory role with the help of distributed energy systems, and track renewable energy generation through supply-side sites, thereby achieving self-balancing within the energy alliance. However, the dispatch of geographically distributed energy alliances relies on the transmission network for power transmission. When the power of new energy is large, the system faces the risk of transmission congestion. Line congestion will lead to serious "wind abandonment" and "light abandonment" in the system, which is not conducive to the efficient use of new energy. The existing methods to alleviate congestion are implemented by power system operators and are not applicable to energy alliances of third-party entities.

[0004] It can be seen that the existing congestion relief measures cannot effectively solve the uncertainty problem of line transmission congestion in the transmission network, which greatly affects the economy and robustness of scheduling under the risk of transmission congestion in the energy alliance. Summary of the invention

[0005] The purpose of the present invention is to provide a risk avoidance scheduling method and system for a geographical distributed energy alliance, so as to solve the technical problem that the existing congestion relief measures cannot effectively solve the uncertainty problem of line transmission congestion in the transmission network, which greatly affects the economy and robustness of scheduling under the risk of transmission congestion of the energy alliance.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a risk avoidance scheduling method for a geographical distributed energy alliance, comprising:

[0008] Obtaining equipment parameters, meteorological parameters, load parameters and economic parameters of a geographical distributed energy alliance; wherein the geographical distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user;

[0009] Based on equipment parameters, meteorological parameters, load parameters and economic parameters, a deterministic model of self-balancing dispatch of energy alliance is constructed with the goal of maximizing the internal benefits of geographical distributed energy alliance.

[0010] Solve the energy alliance self-balancing dispatch deterministic model and obtain the deterministic solution under the predicted value parameters;

[0011] Based on the energy alliance self-balancing dispatch deterministic model and combined with the information gap decision theory, a risk dispatch model is established;

[0012] 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.

[0013] Preferably, the flexible controllable load is carried by 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; wherein the battery energy storage system, the electric boiler, the power-to-gas device and the compression refrigerator are connected and coordinated through the same busbar, and are used to connect the internal power 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 inlet of the absorption refrigerator; the output of the absorption refrigerator and the compression refrigerator is 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.

[0014] Preferably, the equipment parameters include operating parameters of a wind power generation system, a photovoltaic power generation system and a 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 the day-ahead predicted electricity load of large power users, the self-used hydrogen, electricity, cooling and heating loads of flexible loads, and the day-ahead predicted node injection power information of each node of the external power grid;

[0017] 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;

[0018] The energy alliance self-balancing dispatch deterministic model includes 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] max I=RC g -C fl -C trans

[0021]

[0022] Among them, R represents the revenue from selling electricity; I represents the revenue from selling electricity R and the cost of power generation C g , Flexible load operation cost C fl 、Electricity transmission fee C trans The difference; t is the index of the operating period, T is the total number of operating periods; bc is the index of large power users, BC is the set of large power users; is the time-of-use electricity price in period t, is the power load of large power user bc in time period t;

[0023] C g represents the power generation cost; w is the index of the wind power generation system, W is the set of wind power generation systems, s is the index of the photovoltaic power generation system, S is the set of photovoltaic power generation systems; λ w / λ s are the penalty factors for wind power and photovoltaic power, are the fluctuation factors of wind power / photovoltaic power generation system in time period t, reflecting the abundance of wind and light resources; are the installed capacity of wind power / photovoltaic power generation system in time period t respectively; are respectively the actual transmitted active power of the wind power / photovoltaic power generation system in time period t;

[0024] C fl represents the operating cost; ρ bg is the gas purchase price, ρ PtG,o / ρ CHP,o / They 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 the power-to-gas plant, respectively; The amount of gas consumed for cogeneration equipment; are 0-1 variables representing the charge / discharge state of the energy storage device in time period e, t respectively;

[0025] C trans represents the transmission cost; ρ trans The unit price of the network fee is is the amount of electricity transmitted through the grid during time period t.

[0026] Preferably, the flexible load operation constraints of the energy alliance self-balancing dispatch deterministic model include power-to-gas equipment operation constraints, cogeneration equipment operation constraints, electric boiler operation constraints, absorption refrigerator operation constraints, compression refrigerator operation constraints, energy storage equipment operation constraints and flexible load internal energy balance constraints;

[0027] The operation constraints of the new energy power generation system are expressed as:

[0028]

[0029] The power balance constraint is expressed as:

[0030]

[0031] Among them, BC is a collection of large electricity users. B is the amount of electricity sold by the new energy power generation system to the large power user bc during period t, i.e., the power demand of the large power user; o is the set of external grid nodes, is the predicted value of the injected power of external node i in time period t;

[0032] The line transmission constraint is expressed as:

[0033]

[0034]

[0035] in, is the transmission power of line l in period t, G l,w / G l,s / G l,fl / G l,bc / G l,i The power transmission distribution factors of line l about wind power generation system w / photovoltaic power generation system s / flexible load fl / large power user bc / external node i are respectively, and L is the line set of the entire power grid; is the upper limit of the transmission capacity of line l.

[0036] Preferably, the specific steps of establishing a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model and combining the information gap decision theory include:

[0037] Transform the energy alliance self-balancing dispatch deterministic model into a compact matrix form;

[0038] Based on the energy alliance self-balancing dispatch deterministic model in compact matrix form, a prediction error envelope model of the injected power of external grid nodes is established;

[0039] 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, which is used to maximize the robustness of the energy alliance self-balancing scheduling deterministic model under the risk of transmission congestion.

[0040] Preferably, the risk scheduling model is simplified, and the simplified risk scheduling model is solved based on the deterministic solution under the predicted value parameters to obtain the optimal risk avoidance scheduling result of the geographical distributed energy alliance.

[0041] In a second aspect, the present invention provides a risk avoidance scheduling system for a geographical distributed energy alliance, comprising:

[0042] A parameter acquisition module, used to acquire equipment parameters, meteorological parameters, load parameters and economic parameters of a geographical distributed energy alliance; wherein the geographical distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user;

[0043] 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 geographical distributed energy alliance;

[0044] The first model calculation module is used to solve the energy alliance self-balancing dispatch deterministic model to obtain a deterministic solution under the predicted value parameters;

[0045] 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;

[0046] 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.

[0047] In a third aspect, the present invention 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 above-mentioned geographic distributed energy alliance when executing the computer program.

[0048] In a fourth aspect, the present invention provides a computer-readable storage medium, comprising a computer program, which, when executed by a processor, implements the steps of the risk avoidance scheduling method of the above-mentioned geographic distributed energy alliance.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The present invention provides a risk avoidance scheduling method for a geographically distributed energy alliance. The method constructs a self-balancing scheduling deterministic model for an energy alliance with the goal of maximizing internal benefits by acquiring equipment parameters, meteorological parameters, load parameters, and economic parameters. The energy alliance self-balancing scheduling deterministic model can provide a deterministic solution under accurate predicted 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 transmission network, and provide the energy alliance with the optimal risk avoidance scheduling strategy. The use of this scheduling method not only improves the efficient utilization rate of new energy and the flexibility of power system operation, but also significantly enhances the economy and robustness of the energy alliance when facing the risk of transmission congestion, providing a scientific and effective solution for the energy management of third-party entities.

[0051] Preferably, in the present invention, the composition of flexible loads based on distributed energy systems and their connection methods are provided, which helps to more accurately evaluate the regulation capacity and potential of flexible loads, thereby optimizing the internal scheduling of the energy alliance and improving the overall energy efficiency.

[0052] Preferably, in the present invention, specific contents of equipment parameters, meteorological parameters, load parameters and economic parameters, as well as components of the energy alliance self-balancing dispatch deterministic model are provided; detailed data support and theoretical basis are provided for the construction of the model, which helps the model to more accurately reflect the actual situation and improve the accuracy and reliability of dispatch.

[0053] Preferably, in the present invention, the objective function of the energy alliance self-balancing scheduling deterministic model comprehensively considers factors such as electricity sales revenue, power generation costs, flexible load operation costs, and electricity transmission costs; this helps the energy alliance to balance various costs and maximize economic benefits while pursuing maximum internal benefits.

[0054] Preferably, in the present invention, the constraints of the energy alliance self-balancing dispatch deterministic model include flexible load operation constraints, new energy power generation system operation constraints, power balance constraints and line transmission constraints. These constraints ensure the feasibility and safety of dispatch and avoid equipment damage or power grid accidents caused by improper dispatch.

[0055] Preferably, in the present invention, the energy alliance self-balancing dispatch deterministic model is transformed into a compact matrix form, and a prediction error envelope model of the external grid node injection power is established, and a risk dispatch model is constructed in combination with the information gap decision theory. This helps to improve the robustness and adaptability of the model when facing the risk of transmission congestion and ensure the reliability of dispatch.

[0056] Preferably, in the present invention, by simplifying the risk scheduling model and solving it based on the deterministic solution under the predicted value parameters, the optimal risk avoidance scheduling result of the geographical distributed energy alliance is obtained; this helps to quickly and accurately formulate the optimal scheduling strategy in practical applications, and improve the operating efficiency and economic benefits of the energy alliance. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 A typical structural plane topology diagram of an energy alliance and a typical internal structure schematic diagram of a flexible load provided in an embodiment of the present invention;

[0058] Figure 2 A schematic diagram of a process flow of a risk avoidance scheduling method for a geographically distributed energy alliance provided by an embodiment of the present invention;

[0059] Figure 3 The wind power generation provided by the embodiment of the present invention;

[0060] Figure 4 The photovoltaic power generation provided by the embodiment of the present invention;

[0061] Figure 5 The internal electrical load of the flexible load provided by the embodiment of the present invention;

[0062] Figure 6 The hydrogen load inside the flexible load provided by the embodiment of the present invention;

[0063] Figure 7 The internal heat load of the flexible load provided by the embodiment of the present invention;

[0064] Figure 8 The internal cooling load of the flexible load provided by the embodiment of the present invention;

[0065] Fig. 9 The power load of a large power user provided by the embodiment of the present invention;

[0066] Fig.10 The external power grid injection power prediction value provided by the embodiment of the present invention;

[0067] Fig.11 A flow chart of a risk avoidance scheduling method for a geographical distributed energy alliance provided by the present invention;

[0068] Fig.12 A schematic structural diagram of a risk avoidance scheduling system for a geographically distributed energy alliance provided by the present invention. DETAILED DESCRIPTION

[0069] Example 1

[0070] As described in the background technology, currently, the scheduling of geographical distributed energy alliances relies on the transmission network for electricity transmission. When the amount of renewable energy is large, the system faces the risk of transmission congestion. Line blockage will cause serious "wind abandonment" and "solar abandonment" in the system, which is not conducive to the efficient use of renewable energy. The existing methods to alleviate congestion are implemented by power system operators and are not suitable for energy alliances of third-party entities.

[0071] In order to solve the above problems, the present invention provides a risk-avoidance scheduling method for a geographically distributed energy alliance. The method combines the characteristics of wind and solar new energy and flexible loads, considers a new structure of an energy alliance with new energy power generation systems, flexible loads and large electricity users, and aims at the uncertainty of line transmission congestion in the transmission network. A risk-avoidance scheduling method for the energy alliance is proposed, which improves the economy and robustness of the energy alliance facing the risk of transmission congestion.

[0072] It can be seen that in order to improve the flexibility of the system, this embodiment studies the scheduling problem of an energy alliance composed of geographically distributed new energy power generation systems, flexible loads and large electricity users, proposes a collaborative scheduling model that integrates the operation of multiple distributed resources, and adopts information gap decision theory to consider the risk of transmission congestion. A risk-averse scheduling method is proposed to deal with the uncertainty of node injection power in the transmission network, which provides a scientific idea for large-scale and orderly access of new energy to the power grid and promotes the construction of a clean, low-carbon new power system.

[0073] The present embodiment is further explained and illustrated below in conjunction with the accompanying drawings:

[0074] like Figure 1 As shown, this embodiment provides a geographical distributed energy alliance, which is composed of a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user. Among them: the flexible controllable load uses the distributed energy system as a carrier, has internal electricity, cold, heat and gas load (hydrogen load) requirements, and is composed of 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 and coordinated through the same bus to connect the internal power 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 inlet of the absorption refrigerator input port; the output of the absorption refrigerator and the compression refrigerator are connected to the input port of the cold storage tank. The gas storage tank, heat storage tank and cold storage tank are respectively connected to the gas load, heat load and cold load demand sides to provide corresponding types of energy for the flexible and controllable loads.

[0075] 1) The specific structural characteristics of the geographical distributed energy alliance are as follows:

[0076] (1) A wind power generation system consists of a group of wind turbines, inverters, collection lines and other auxiliary equipment, which can convert wind energy into electrical energy;

[0077] (2) Photovoltaic power generation system consists of photovoltaic arrays, inverters, collection lines and other auxiliary equipment, which can convert solar energy into electrical energy;

[0078] (3) The battery energy storage system consists of battery packs, battery management systems, power conversion systems, collection lines and other auxiliary equipment, and is used for the storage, conversion and release of electrical energy;

[0079] (4) Cogeneration equipment generates electricity and heat simultaneously, using gas as a raw material to generate electricity and recovering and using the heat emitted during power generation to supply the heat load;

[0080] (5) The power-to-gas device consists of a tank, an anode and a cathode, and can generate gas by chemical reaction;

[0081] (6) The heat recovery device is used to recover the heat energy generated during the operation of the power-to-gas equipment and the cogeneration equipment, and then pass the recovered heat energy into the heat storage tank for storage;

[0082] (7) Electric boiler is a thermal equipment that converts electrical energy into thermal energy, including necessary safety accessories and heating pipes, controllers, water pumps, etc., which can generate heat at room temperature and store it in a heat storage tank;

[0083] (8) Absorption refrigerator is a refrigeration device that absorbs heat energy and converts it into cold energy. It relies on the action of the absorber and generator group to complete the refrigeration cycle and can use heat energy as a source of refrigeration at room temperature;

[0084] (9) A compression refrigerator is a refrigeration device that converts electrical energy into cold energy, including necessary safety accessories, condensers, throttle valves, etc., and can use electrical energy for refrigeration at room temperature;

[0085] (10) The gas storage tank is a pressure vessel for storing gas. It stores gas at high pressure and is equipped with a compressor, including necessary safety accessories and pressure detection and display instruments. It can quickly charge and discharge gas at room temperature to supply the gas load inside the flexible controllable load;

[0086] (11) The heat storage tank is a container for storing liquid hot water, including necessary safety accessories and temperature detection and display instruments, etc. It can quickly charge and discharge hot water at room temperature and supply the heat load inside the flexible controllable load.

[0087] (12) A cold storage tank is a container for storing liquid cold water, including necessary safety accessories and temperature detection and display instruments, etc. It can quickly charge and discharge cold water at room temperature and supply the heat load inside the flexible controllable load.

[0088] 2) The specific operating characteristics of the geographical distributed energy alliance are as follows:

[0089] (1) Wind power generation systems and photovoltaic power generation systems convert wind energy and solar energy into electrical energy. Through direct load control technology (DLC), flexible and controllable loads track the output of new energy sources to achieve balance within the energy alliance.

[0090] (2) Use the power network to transmit the electricity generated by wind power generation systems and photovoltaic power generation systems to flexible loads and large power users.

[0091] (3) The electricity transmitted by the power grid, the battery energy storage system and the electricity generated by the cogeneration equipment can be fed into the power-to-gas equipment, electric boilers and compression refrigerators to convert the electricity into gas, heat and cold respectively, and then store the converted energy in the corresponding energy storage device.

[0092] (3) When the power grid implements industrial and commercial peak and valley electricity prices and provincial electricity transmission and distribution prices, flexible loads can interact with wind and solar energy as demand-side flexible resources. The energy alliance pays the power grid for electricity transmission fees to enable the new energy power generation system to transmit electricity to supply flexible loads and large power users. The new energy power generation can be sent to large power users to obtain electricity sales revenue. The dispatching costs of flexible loads, the "wind and solar abandonment" of new energy power generation systems, and the electricity transmission costs are regarded as the costs of the energy alliance. If the power that can be transmitted through the power grid is sufficient, the flexible load can flexibly adjust the external characteristics of the power with the help of its own internal multi-media energy storage to track the output of new energy; if the power that the energy alliance can transmit is limited due to grid line congestion, the new energy power generation system will inevitably have a large amount of "wind and solar abandonment". The needs of large power users must be met first to ensure revenue. Flexible loads can purchase gas for power generation and dispatch multiple types of energy production equipment and energy storage devices to meet their own load needs.

[0093] like Figure 2 As shown, this embodiment provides a risk-averse self-balancing scheduling method for a geographical distributed energy alliance, the purpose of which is to improve the energy alliance's ability to cope with blocking risks, meet the safe operation of the power system and the supply of various load demands, and optimize the scheduling of flexible load internal cogeneration equipment, power-to-gas equipment, heat recovery devices, electric boilers, absorption refrigerators, compression refrigerators, gas storage tanks, heat storage tanks, cold storage tanks and battery energy storage systems, track the output of new energy to transmit more new energy power generation, and achieve the optimal economy of energy alliance scheduling under blocking risks; (Note here that in this embodiment, it is assumed that the compressor is an auxiliary equipment of the gas storage tank, and its cost is calculated together with the gas storage tank, and it is no longer scheduled separately). This scheduling method specifically includes the following steps:

[0094] S1: Obtain relevant information required for a risk-averse dispatch method for a geographical distributed energy alliance, including:

[0095] (1) Equipment parameters, such as operating parameters of wind power generation systems, photovoltaic power generation systems, cogeneration equipment, power-to-gas equipment, heat recovery devices, electric boilers, absorption refrigerators, compression refrigerators, gas storage tanks, heat storage tanks, cold storage tanks, and battery energy storage systems;

[0096] (2) meteorological parameters, such as historical fluctuation factors of wind and light resources;

[0097] (3) Load parameters, such as the day-ahead forecast of electricity consumption by large power users, the self-use hydrogen, electricity, cooling and heating loads of flexible loads, and the day-ahead forecast of node injection power information of each node in the external power grid;

[0098] (4) Economic parameters, such as the penalty for “abandoning wind and solar power” in new energy power generation systems, the operating costs of various energy equipment, the grid’s time-of-use electricity price, and the electricity transmission and distribution price.

[0099] S2: Based on the historical wind and light resource fluctuation factors, load parameters, equipment parameters and economic parameters in step 1, a deterministic model for self-balancing scheduling of the energy alliance is constructed:

[0100] 1) Objective function

[0101] max I=RC g -C fl -C trans (1)

[0102]

[0103] (1) The revenue from electricity sales (Formula (2)) is the revenue from electricity trading between the new energy power generation system and large power users. Where I represents the revenue from electricity sales R and the power generation cost C g , Flexible load operation cost C fl 、Electricity transmission fee C trans The difference; t is the index of the operating period, T is the total number of operating periods; bc is the index of large power users, BC is the set of large power users; is the time-of-use electricity price in period t, is the power load of large power user bc in time period t.

[0104] (2) The power generation cost (Formula (3)) is the operating cost of the new energy power generation system due to wind and solar power abandonment. Where w is the index of the wind power generation system, W is the set of wind power generation systems, s is the index of the photovoltaic power generation system, and S is the set of photovoltaic power generation systems. w / λ s are the penalty factors for wind power and photovoltaic power, are the fluctuation factors of wind power / photovoltaic power generation system in time period t, reflecting the abundance of wind and light resources; are the installed capacity of wind power / photovoltaic power generation system in time period t respectively; are the actual transmitted active power of the wind power / photovoltaic power generation system in time period t. The operating cost of the new energy power generation system is the sum of the penalty factor and the amount of abandoned power, and the amount of abandoned power is the difference between the wind and solar power generation and the actual transmitted active power.

[0105] (3) The operating cost (Formula (4)) is the sum of the operating cost of each energy device within the flexible load and the gas purchase cost. bg is the gas purchase price, ρ PtG,o / ρ CHP,o / They are the operating costs of power-to-gas equipment / cogeneration equipment / energy storage equipment; and are the volumes of gas purchased from the energy market and generated in the power-to-gas plant, respectively; The amount of gas consumed for cogeneration equipment; are 0-1 variables representing the charge / discharge state of the energy storage device in time period t.

[0106] (4) Transmission cost (Formula (5)) is the transmission fee generated by the new energy power generation system when transmitting electricity through the external power grid. trans The unit price of the network fee is is the amount of electricity transmitted through the grid during time period t.

[0107] 2) Flexible load operation constraints

[0108] The operation of flexible loads must meet a series of constraints:

[0109] (1) Power-to-gas equipment operation constraints

[0110] The power-to-gas device can convert electrical energy into gas through chemical reactions, and during its operation, electrical energy is also converted into heat energy, which is realized by the heat recovery device (note that the heat recovery device of the present invention is used to recover the heat generated during the operation of the power-to-gas device, and the relevant constraints are given together with the relevant equipment that generates waste heat, and its operation constraints are no longer given separately). The power-to-gas and power-to-heat conversion equations are:

[0111]

[0112] in, are the electricity-to-gas / electricity-to-heat conversion efficiency; k p-g / k p-f They are the electricity-to-gas / electricity-to-heat conversion performance coefficients of the power-to-gas equipment; is the amount of electricity used by the power-to-gas equipment during time period t; ft PtG The heat energy generated during the operation of the power-to-gas equipment is in period t.

[0113] In addition, the operation of power-to-gas equipment is also subject to the capacity constraints of the equipment:

[0114]

[0115] in, is a 0-1 variable indicating the working state of the power-to-gas device during period t; They are respectively the upper / lower limits of the power consumption of the power-to-gas equipment in time period t.

[0116] To avoid the simultaneous operation of the power-to-gas equipment and the cogeneration equipment, and the operation of the gas storage equipment is related to the operating status of the gas generation / consumption equipment, the operation of the power-to-gas equipment is subject to the following constraints:

[0117]

[0118] in: A 0-1 variable indicating the charging status of the gas storage device at time period t.

[0119] (2) Operation constraints of cogeneration equipment

[0120] 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:

[0121]

[0122] in, The combined heat and power plant generates electricity for time period t; are the gas-electricity / gas-heat conversion efficiency of cogeneration equipment; k g-p / k g-f are the gas-to-electricity / gas-to-heat conversion performance coefficients, respectively; is the gas consumed by the power-to-gas equipment during period t; f t CHP The heat energy generated during the operation of the cogeneration equipment is in time period t.

[0123] In addition, the operation of cogeneration equipment is also subject to the capacity constraints of the equipment:

[0124]

[0125] in, is a 0-1 variable indicating the working status of the cogeneration equipment during period t; are the upper / lower limits of the amount of electricity generated by the cogeneration equipment during time period t.

[0126] Similarly, similar to the power-to-gas plant, the operation status of the cogeneration plant is subject to the following constraints:

[0127]

[0128] in: It is a 0-1 variable indicating the energy release state of the gas storage device during period t.

[0129] (3) Electric boiler operation constraints

[0130] Electric boilers convert electrical energy into thermal energy by heating water. The electrical-thermal conversion equation is:

[0131]

[0132] Among them, f t eb is the heat output of the electric boiler in period t; η eb is the electricity-heat conversion efficiency of the electric boiler; is the electricity consumed by the electric boiler during period t.

[0133] In addition, the operation of electric boilers is also subject to the capacity constraints of the equipment:

[0134]

[0135] in, It is the upper limit of the heat energy generated by the electric boiler in time period t.

[0136] (4) Absorption Chiller Operation Constraints

[0137] The absorption chiller uses heat energy as the driving energy to achieve refrigeration, and its heat-cold conversion equation is:

[0138]

[0139] in, The absorption chiller produces cold energy for period t; η ac is the conversion efficiency of the absorption chiller; k f-c is the heat-cooling conversion performance coefficient; f t ac is the heat energy consumed by the absorption refrigerator during period t.

[0140] In addition, the operation of absorption chillers is also subject to the capacity constraints of the equipment:

[0141]

[0142] in, is the upper limit of the heat energy generated by the absorption refrigerator in time period t.

[0143] (5) Compression Refrigerator Operation Constraints

[0144] Compression refrigerators use electrical energy to achieve cooling effect by compressing and relaxing the refrigerator. The electricity-to-cold conversion equation is:

[0145]

[0146] in, is the cooling capacity of the compression refrigeration machine during period t; η cr is the conversion efficiency of the compression refrigerator; k p-c is the heat-to-cold conversion performance coefficient; is the power consumed by the compression refrigerator during time period t.

[0147] In addition, the operation of compression chillers is also subject to the capacity constraints of the equipment:

[0148]

[0149] in, The upper limit of the cooling capacity of the compression refrigeration machine in time period t

[0150] (6) Energy storage equipment operation constraints

[0151] Energy storage equipment includes battery energy storage, gas storage tanks, heat storage tanks and cold storage tanks, which are electric energy, gas, heat energy and cold energy storage devices respectively. The operating constraints of the energy storage equipment are written as general expressions. The energy storage equipment set is denoted as E = @{ess, g, f, c}, and the set elements represent battery energy storage, gas storage tanks, heat storage tanks and cold storage tanks respectively.

[0152] Energy storage devices cannot be charged or discharged and are limited to a single charge and discharge state as follows:

[0153]

[0154] Secondly, the operation of energy storage equipment is also subject to the power constraints of the equipment:

[0155]

[0156] in, They are respectively the charging / discharging amount of energy storage device e in time period t; They are the upper limits of charging / discharging of energy storage devices respectively.

[0157] In addition, each energy storage device satisfies the material flow balance equation and energy storage capacity constraints of the energy system:

[0158]

[0159] Among them, M e,t is the capacity state of energy storage device e in time period t, are the charging / discharging efficiency of the energy storage device e, are the upper / lower limits of the capacity of energy storage device e in time period t respectively.

[0160] In order to ensure that the energy storage state at the beginning and end of the dispatch is the same, the energy storage equipment should also meet the following energy storage state constraints at the beginning and end:

[0161]

[0162] (7) Internal energy balance constraints of flexible loads

[0163] There are multiple energy sources inside the flexible load, and its external characteristics are electrical characteristics, expressed as:

[0164]

[0165] in, For flexibility to meet internal electrical loads.

[0166] In addition, multiple types of energy are converted into each other within the flexible load, and the gas, heat, and cold energy subsystems meet the following energy balances:

[0167]

[0168] in, They are the air / heat / cooling demands within the flexible load respectively.

[0169] 3) Operation constraints of new energy power generation systems

[0170] The system output of wind power generation system and photovoltaic power generation system is mainly determined by installed capacity and natural resource conditions. The active output constraints that wind power generation system and photovoltaic power generation system need to meet are as follows:

[0171]

[0172] 4) Power balance constraints

[0173] The power grid to which the Geographic Distributed Energy Alliance is connected is called the external power grid. The power supply system of the Geographic Distributed Energy Alliance and the external power grid must satisfy the power balance equation respectively:

[0174]

[0175] Among them, BC is a collection of large electricity users. B is the amount of electricity sold by the new energy power generation system to the large power user bc during period t, i.e., the power demand of the large power user; o is the set of external grid nodes, is the predicted value of the injected power of external node i in time period t.

[0176] 5) Line transmission constraints

[0177] The power transmission in the power grid is subject to the line transmission security constraints. The line transmission power expression and transmission capacity constraints based on the power transmission distribution factor are as follows:

[0178]

[0179] in, is the transmission power of line l in period t, G l,w / G l,s / G l,fl / G l,bc / G l,i The power transmission distribution factors of line l about wind power generation system w / photovoltaic power generation system s / flexible load fl / large power user bc / external node i are respectively, and L is the line set of the entire power grid; is the upper limit of the transmission capacity of line l.

[0180] S3: Solve the energy alliance self-balancing dispatch deterministic model in step 2 and obtain a deterministic solution under the predicted value parameters.

[0181] S4: Based on the deterministic model of energy alliance self-balancing scheduling, a risk scheduling model based on information gap decision theory (IGDT) is established.

[0182] S401: To avoid redundancy in subsequent content, a compact matrix form of the deterministic model is given:

[0183]

[0184] stAx≥b (38)

[0185] -Ex+Fy≥0 (39)

[0186]

[0187] Ky≥k (41)

[0188]

[0189] in, For the predicted value The objective function (37) corresponds to equations (1)-(5), where x and y are 0-1 variables and continuous variables, respectively; equation (38) is the related constraint of variable x, corresponding to constraints (9), (13) and (21); equation (39) is the coupling constraint of variables x and y, corresponding to constraints (8), (12) and (22)-(23); equation (39) is the relationship between variable y and predicted value The relationship between corresponds to constraints (34) and (35), and equation (42) represents the remaining constraints in the deterministic model.

[0190] S402: Establishing a prediction error envelope model of the external grid node injected power:

[0191]

[0192] Among them, α L To determine the node power prediction value, the risk boundary is uncertain. and actual value According to the linear relationship between the node power and the line power in equation (35), for the constant The transmission congestion risk is directly determined by α L Decision, α L The larger the size, the higher the probability of blocking.

[0193] S403: Furthermore, a risk-averse scheduling model is constructed based on the information gap decision theory, which can maximize the robustness of the energy alliance scheduling model under the risk of transmission congestion:

[0194]

[0195] Ax≥b (46)

[0196] -Ex+Fy≥0 (47)

[0197] Hy+JP=h (48)

[0198] Ky≥k (49)

[0199]

[0200] Among them, Λ0 is the expected economic benefit under uncertainty, which is the maximum benefit value of the deterministic solution under the predicted value parameter, σ is the offset factor below the expected benefit of the energy alliance (indicating the acceptance limit of the scheduling decision-maker for benefits lower than the expected), and equation (45) is defined as the "benefit lower bound" constraint to ensure that the total benefit of the energy alliance scheduling is higher than the benefit lower limit (1-σ)Λ0. Note that the risk scheduling model is actually a two-level optimization problem. The upper optimization problem is to maximize the uncertain risk boundary α L The objective is to satisfy the constraints (45)-(49); the lower optimization problem (51) takes into account the uncertainty set Affects the economic benefits of the energy alliance under the worst-case scenario.

[0201] S404: Further, simplify the risk aversion scheduling model. Obviously, when the external node injection power reaches the risk critical value (i.e. ), the lowest economic benefit will be obtained. Therefore, equations (45) and (48) can be equivalently replaced by the following equations, which can transform the two-layer optimization problem into a single-layer optimization form that is easier to solve:

[0202] c T x+d T y≥(1-σ)Λ(52)

[0203]

[0204] It can be seen that equations (44), (46)-(47), (49)-(50) and (52)-(53) constitute the single-layer mixed integer optimization form of the risk-averse scheduling model.

[0205] S5: Solve the energy alliance risk aversion scheduling model of step S4 to obtain the optimal risk aversion scheduling result of the energy alliance.

[0206] The scheduling method provided in this embodiment is specifically implemented as follows:

[0207] Taking the IEEE 30-node system as an example, there are 30 nodes and 41 lines. Figure 1 The diagram of the connection between the energy alliance and the external power grid shows that three wind power generation systems and four photovoltaic power generation systems are set up at nodes 6, 22, 25, 4, 5, 9 and 27 respectively. Two large electricity users are at nodes 11 and 13, and the flexible load is at node 28. In this embodiment, the gas in the flexible controllable load is hydrogen, the power-to-gas equipment is an electrolyzer, the cogeneration equipment is a fuel cell, and the gas storage tank is a hydrogen storage tank. The relevant information required for a risk avoidance scheduling method for a geographically distributed energy alliance is obtained. Tables 1 and 2 respectively show the main economic parameters of the internal energy conversion equipment and energy storage equipment of the flexible load. Table 3 shows the time-of-use electricity price data in the area where the energy alliance is located. The remaining parameters required for risk scheduling are shown in Table 4.

[0208] Table 1 Main parameters of flexible load internal energy conversion equipment

[0209]

[0210] Table 2 Main parameters of energy storage system

[0211]

[0212]

[0213] Table 3 Time-of-use electricity price data

[0214]

[0215] Table 4 Other parameters required for this embodiment

[0216]

[0217] In addition to the above parameters, the output of the new energy power generation system is as follows Figure 3 As shown in the figure, the various types of load requirements within the flexible load are as follows Figure 4-8 As shown; the load demands of two large power users are as follows Fig. 9 As shown, there are 20 external nodes in total. Fig.10 Only the node injection power prediction values ​​of randomly selected nodes 8, 14, and 15 are displayed.

[0218] 1) Example test setup

[0219] Case 1: Deterministic Scheduling

[0220] Case 2: Risk-averse scheduling (σ=0.12)

[0221] Based on the parameters of the above embodiment, a case test is performed, including the deterministic scheduling Case 1 (solving equations (37)-(42)) and risk scheduling Case 2 (solving the risk scheduling model obtained in step 4) mentioned in the steps. In order to better compare the effectiveness of the invention method, the parameters are changed on the basis of the deterministic scheduling model to set a comparison case Case 1#: the upper limit of the transmission power and the lower limit of the purchase of hydrogen of Case 1# are set to the scheduling results of Case 1, and the node injection power value is set to Set to the solution result of Case 2 Then solve equations (37)-(42).

[0222] 2) Example results

[0223] The method of the present invention is used to solve the example.

[0224]

[0225] Deterministic dispatch uses the predicted value for optimized dispatch, with a total benefit of 135,217.32 yuan. At this time, the flexible load does not incur hydrogen purchase costs, indicating that wind power and photovoltaic power generation fully meet the load demand and achieve balance within the energy alliance. Compared with deterministic dispatch, the grid access fee of risk dispatch is reduced by 3,034.94 yuan, and the cost of abandoned power is increased by 4,134.8 yuan. At this time, the flexible load needs to purchase hydrogen from the energy market to meet energy demand, and the cost of purchasing hydrogen is 12,860.91 yuan. The risk-averse dispatch benefit after considering the blocking risk is 16,226.08 yuan lower than the deterministic dispatch.

[0226] The results of Case 1# are further analyzed to illustrate the advantages of the proposed risk-averse scheduling method. When the energy alliance faces the congestion risk in Case 2, the benefits of using the deterministic model scheduling are lower than those of risk scheduling Case 2. This shows that the risk-averse scheduling method based on IGDT can effectively hedge the risk of line transmission congestion and has certain economic benefits.

[0227] In summary, the risk avoidance scheduling method for the geographical distributed energy alliance provided in this embodiment has the following advantages over the existing scheduling methods or congestion relief measures:

[0228] This dispatching method introduces the structure of geographical distributed energy alliance for the first time, that is, through the agreement cooperation of new energy power generation system, flexible controllable load and large power users, an energy alliance with geographical distribution is formed. Secondly, the self-balancing dispatching of energy alliance can be based on direct load control technology, dispatching the internal equipment of flexible load to track the fluctuation of new energy, realizing the energy balance within the energy alliance, and thus absorbing new energy; compared with the general energy alliance, the distributed energy system is the carrier of flexible controllable load, with multi-energy conversion equipment and multi-media energy storage system inside, which can improve the flexibility of user-side regulation, so as to play the role of flexible load in energy alliance. When there is too much electricity transmitted through the power grid, the energy alliance can take advantage of its own multi-energy conversion and store electric energy in various energy forms; when the amount of electricity transmitted to the flexible load is small, the flexible load can purchase gas from the energy market and use gas to generate electricity to meet the load demand. Finally, considering the risk aversion dispatching model of transmission congestion uncertainty, the energy alliance can ensure the economy of its own dispatching when the power grid is blocked. This dispatching method provides a risk dispatching scheme facing the uncertainty of transmission congestion, and the use of this method can effectively improve the robustness and economy of energy alliance dispatching under the risk of transmission congestion.

[0229] Example 2

[0230] like Fig.11 As shown, this embodiment provides a risk avoidance scheduling method for a geographical distributed energy alliance, including the following steps:

[0231] Obtaining equipment parameters, meteorological parameters, load parameters and economic parameters of a geographical distributed energy alliance; wherein the geographical distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user;

[0232] Based on equipment parameters, meteorological parameters, load parameters and economic parameters, a deterministic model of self-balancing dispatch of energy alliance is constructed with the goal of maximizing the internal benefits of geographical distributed energy alliance.

[0233] Solve the energy alliance self-balancing dispatch deterministic model and obtain the deterministic solution under the predicted value parameters;

[0234] Based on the energy alliance self-balancing dispatch deterministic model and combined with the information gap decision theory, a risk dispatch model is established;

[0235] 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.

[0236] like Fig.12 As shown, this embodiment also provides a risk avoidance scheduling system for a geographic distributed energy alliance, including: a parameter acquisition module, used to obtain equipment 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 large power user; a first model construction module, used to construct an energy alliance self-balancing scheduling deterministic model based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal benefits of the geographic distributed energy alliance; a first model calculation module, used to solve the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under the predicted value parameters; a second model construction module, used to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model in combination with the information gap decision theory; a second model calculation module, used to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameters, to obtain the optimal risk avoidance scheduling result of the geographic distributed energy alliance.

[0237] The present invention also provides a device, comprising: a memory for storing a computer program; and a processor for implementing the steps of the risk avoidance scheduling method of the geographical distributed energy alliance when executing the computer program.

[0238] When the processor executes the computer program, the steps of risk-averse scheduling of the above-mentioned geographic distributed energy alliance are implemented, for example: obtaining equipment parameters, meteorological parameters, load parameters and economic parameters of the geographic distributed energy alliance; wherein the geographic distributed energy alliance includes wind power generation systems, photovoltaic power generation systems, flexible controllable loads and large power users; based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal benefits of the geographic distributed energy alliance, constructing a self-balancing scheduling deterministic model of the energy alliance; solving the self-balancing scheduling deterministic model of the energy alliance to obtain a deterministic solution under the predicted value parameters; based on the self-balancing scheduling deterministic model of the energy alliance, combining the information gap decision theory, establishing a risk scheduling model; based on the deterministic solution under the predicted value parameters, solving the risk scheduling model based on the information gap decision theory, and obtaining the optimal risk-averse scheduling result of the geographic distributed energy alliance.

[0239] Alternatively, the processor implements the functions of each module in the above system when executing the computer program, for example: a parameter acquisition module, which is used to obtain equipment 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, which is used to construct an energy alliance self-balancing scheduling deterministic model based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal benefits of the geographic distributed energy alliance; a first model calculation module, which is used to solve the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under the predicted value parameters; a second model construction module, which is used to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model in combination with the information gap decision theory; 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 parameters, to obtain the optimal risk avoidance scheduling result of the geographic distributed energy alliance.

[0240] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing preset functions, and the instruction segments are used to describe the execution process of the computer program in the risk aversion scheduling device of the geographical 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 each module are as follows: a parameter acquisition module, used to obtain equipment 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, used to construct an energy alliance self-balancing scheduling deterministic model based on equipment parameters, meteorological parameters, load parameters and economic parameters, with the goal of maximizing the internal benefits of the geographic distributed energy alliance; a first model calculation module, used to solve the energy alliance self-balancing scheduling deterministic model to obtain a deterministic solution under the predicted value parameters; a second model construction module, used to establish a risk scheduling model based on the energy alliance self-balancing scheduling deterministic model in combination with the information gap decision theory; a second model calculation module, used to solve the risk scheduling model based on the information gap decision theory based on the deterministic solution under the predicted value parameters, to obtain the optimal risk avoidance scheduling result of the geographic distributed energy alliance.

[0241] The risk aversion scheduling device of the geographic distributed energy alliance can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The risk aversion scheduling device of the geographic distributed energy alliance may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above is an example of a risk aversion scheduling device of a geographic distributed energy alliance, and does not constitute a limitation on the risk aversion scheduling device of a geographic distributed energy alliance. It may include more components than the above, or a combination of certain components, or different components. For example, the risk aversion scheduling device of the geographic distributed energy alliance may also include input and output devices, network access devices, buses, etc.

[0242] The processor may be a central processing unit (CPU), or 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 the processor may be any conventional processor, etc. The processor is the control center of the risk aversion scheduling of the geographic distributed energy alliance, and uses various interfaces and lines to connect various parts of the risk aversion scheduling equipment of the entire geographic distributed energy alliance.

[0243] The memory can be used to store the computer program and / or module, and the processor implements various functions of the risk aversion scheduling device of the geographic distributed energy alliance by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory.

[0244] The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (SecureDigital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0245] The present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the risk avoidance scheduling method of a geographical distributed energy alliance are implemented.

[0246] If the modules / units integrated in the risk-averse scheduling system of the geographic distributed energy alliance are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0247] Based on such understanding, the present invention implements all or part of the processes in the risk aversion scheduling method of the above-mentioned geographical distributed energy alliance, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and when the computer program is executed by the processor, the steps of the risk aversion scheduling method of the above-mentioned geographical distributed energy alliance 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 preset intermediate form, etc.

[0248] The computer-readable storage 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), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0249] It should be noted that the content contained 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 legislation and patent practice, computer-readable storage media do not include electrical carrier signals and telecommunication signals.

[0250] The above embodiment is only one of the implementation methods that can realize the technical solution of the present invention. The scope of protection claimed by the present invention is not limited only to this embodiment, but also includes changes, replacements and other implementation methods that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention.

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 geographical distributed energy alliance; wherein the geographical distributed energy alliance includes a wind power generation system, a photovoltaic power generation system, a flexible controllable load and a large power user; Based on equipment parameters, meteorological parameters, load parameters and economic parameters, a deterministic model of self-balancing dispatch of energy alliance is constructed with the goal of maximizing the internal benefits of geographical 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 the 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.

2. A 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; wherein the battery energy storage system, the electric boiler, the power-to-gas device and the compression refrigerator are connected and coordinated through the same busbar, and are used to connect the internal power 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 output of the absorption refrigerator and the compression refrigerator is 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 equipment parameters include operating parameters of a wind power generation system, a photovoltaic power generation system, and a 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 predicted electricity load of large power users, the self-used hydrogen, electricity, cooling and heating loads of flexible loads, and the day-ahead predicted node injection power information of each node of 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 objective function, flexible load operation constraints, new energy power generation system operation constraints, power balance constraints and line transmission constraints.

4. A risk avoidance scheduling method for a geographically distributed energy alliance according to claim 3, characterized in that: The objective function of the energy alliance self-balancing dispatch deterministic model is expressed as: max I=R-C g -C fl -C trans Among them, R represents the revenue from selling electricity; I represents the revenue from selling electricity R and the cost of power generation C g , Flexible load operation cost C fl 、Electricity transmission fee C trans The difference; t is the index of the operating period, T is the total number of operating periods; bc is the index of large power users, BC is the set of large power users; is the time-of-use electricity price in period t, is the power load of large power user bc in time period t; C g represents the power generation cost; w is the index of the wind power generation system, W is the set of wind power generation systems, s is the index of the photovoltaic power generation system, S is the set of photovoltaic power generation systems; λ w / λ s are the penalty factors for wind power and photovoltaic power, are the fluctuation factors of wind power / photovoltaic power generation system in time period t, reflecting the abundance of wind and light resources; are the installed capacity of wind power / photovoltaic power generation system in time period t respectively; are respectively the actual transmitted active power of the wind power / photovoltaic power generation system in time period t; C fl represents the operating cost; ρ bg is the gas purchase price, They 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 the power-to-gas plant, respectively; The amount of gas consumed for cogeneration equipment; are 0-1 variables representing the charge / discharge state of the energy storage device in time period e, t respectively; C trans represents the transmission cost; ρ trans The unit price of the network fee is is the amount of electricity transmitted through the grid during time period t.

5. A risk avoidance scheduling method for a geographically distributed energy alliance according to claim 4, characterized in that: The flexible load operation constraints of the energy alliance self-balancing dispatch deterministic model include power-to-gas equipment operation constraints, cogeneration equipment operation constraints, electric boiler operation constraints, absorption refrigerator operation constraints, compression refrigerator 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: Among them, BC is a collection of large electricity users. B is the amount of electricity sold by the new energy power generation system to the large power user bc during period t, i.e., the power demand of the large power user; o is the set of external grid nodes, is the predicted value of the injected power of external node i in time period t; The line transmission constraint is expressed as: in, is the transmission power of line l in period t, G l,w / G l,s / G l,fl / G l,bc / G l,i The power transmission distribution factors of line l about wind power generation system w / photovoltaic power generation system s / flexible load fl / large power user bc / external node i are respectively, and L is the line set of the entire power grid; is the upper limit of the transmission capacity of line l.

6. 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 injected power of external grid nodes 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, which is used to maximize the robustness of the energy alliance self-balancing scheduling deterministic model under the risk of transmission congestion.

7. 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.

8. A risk-avoidance dispatching system for a geographically distributed energy alliance, characterized in that: include: A parameter acquisition module, used to acquire equipment parameters, meteorological parameters, load parameters and economic parameters of a geographical distributed energy alliance; wherein the geographical 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 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 geographical distributed energy alliance; The first model calculation module is used to solve the energy alliance self-balancing dispatch deterministic model to 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.

9. A device, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the risk avoidance scheduling method of the geographical distributed energy alliance described in any one of claims 1 to 7 when executing the computer program.

10. 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 geographic distributed energy alliance as described in any one of claims 1-7.

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