Multi-energy complementary power quantity balancing method and device considering power grid topology, and storage medium

Abstract

The invention discloses a multi-energy complementary electric power and electric quantity balancing method and device considering a power grid topology and a storage medium, and belongs to the technical field of electric power and electric quantity balancing, and the method comprises the steps: simplifying an original power grid topology into a regional interconnected simplified power grid topology; predicting to obtain a wind-solar new energy output curve and a load curve, and determining an electric power and electric quantity constraint condition required to be provided by a non-new energy unit; determining upper and lower limit constraint conditions of output of the thermal power generating unit in a full time zone; constructing a generating capacity constraint condition of the hydropower station according to the seasonal operation cycle of the hydropower station; determining a charge-discharge power constraint condition and a capacity constraint condition of the energy storage system; according to the multiple constraint conditions, in the simplified power grid topology, an optimization problem model with the minimum sum of the unit start-stop cost and the line transmission cost as the target is established; and solving the optimization problem model to obtain a scheduling strategy of the multi-energy complementary power system. The electric power and electric quantity balance effect can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power and electricity balance, and in particular to a multi-energy complementary power and electricity balance method, device and storage medium considering power grid topology. Background Art

[0002] With the transformation of the global energy structure and the promotion of the sustainable development strategy, the power system is facing unprecedented challenges. The traditional power system mainly relies on thermal power generation. With the rapid development of renewable energy such as hydropower, wind power, and solar power, the power system is gradually developing towards multi-energy complementarity. The multi-energy complementary power system improves energy utilization efficiency, enhances the flexibility and reliability of the system by integrating the advantages of different energies, and is of great significance for realizing the clean, efficient, and safe supply of energy. In the multi-energy complementary power system, power and electricity balance is one of the core issues. Power and electricity balance involves the supply-demand matching of the power system, including two aspects: power balance and electricity balance. Power balance focuses on the instantaneous power supply-demand matching of the power system, while electricity balance focuses on the supply-demand balance of the total energy within a certain period of time. In the multi-energy complementary power system, due to the distributed access of renewable energies such as wind power and solar power, the power system to be analyzed for power and electricity balance is more complex, bringing new challenges to the balance calculation.

[0003] For the power and electricity balance calculation of complex large-scale systems, in order to improve the calculation efficiency, the existing power and electricity balance methods often directly ignore the power grid topology and regard all units as connected to the same node. Although directly ignoring the power grid topology greatly improves the calculation efficiency, completely ignoring the power grid topology information will lead to the inconsistency between the balance calculation result and the actual situation, resulting in poor power and electricity balance effect. Summary of the Invention

[0004] The present invention provides a multi-energy complementary power and electricity balance method, device and storage medium considering power grid topology to solve the technical problem that the existing power and electricity balance methods completely ignoring the power grid topology information will lead to the inconsistency between the balance calculation result and the actual situation, resulting in poor power and electricity balance effect.

[0005] The present invention provides a multi-energy complementary power and electricity balance method considering power grid topology, including:

[0006] Simplify the original power grid topology into a regionally interconnected simplified power grid topology according to the power grid scale, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads.

[0007] Based on the source-load prediction program, the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system are predicted. According to the output data in the output curves of wind and solar new energy and the load curve, the power and electricity quantity constraint conditions required to be provided by non-new energy units are determined; wherein, the output data includes the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the output data of loads, the output data of wind turbines, and the output data of photovoltaic units.

[0008] According to the heating demand, the upper and lower limit constraint conditions of the output of thermal power units in the full time zone are determined.

[0009] According to the seasonal operation cycle of the hydropower station, as well as the lower limit of the output of the hydropower unit and the upper limit of the output of the hydropower unit, the power generation constraint conditions of the hydropower station are constructed.

[0010] According to the charge and discharge power of the energy storage system, the charge and discharge power constraint conditions and the capacity constraint conditions of the energy storage system are determined.

[0011] According to the power and electricity quantity constraint conditions, the upper and lower limit constraint conditions of the output of thermal power units, the power generation constraint conditions, the charge and discharge power constraint conditions, and the capacity constraint conditions, based on the simplified power grid topology, an optimization problem model with the lowest total of unit start-stop costs and line transmission costs as the goal is established.

[0012] The optimization problem model is solved to obtain the dispatching strategy of the multi-energy complementary power system. According to the dispatching strategy, the operating states of each unit of the power system are controlled to achieve power and electricity quantity balance.

[0013] Further, the simplifying the original power grid topology into a regionally interconnected simplified power grid topology according to the power grid scale, as well as the active power output of the power supplies connected to all nodes in the same partition and the node load, includes:

[0014] When the number of power grid nodes is less than or equal to the preset threshold, the original power grid topology is retained without aggregation processing; when the number of power grid nodes is greater than the preset threshold, aggregation operations are performed based on the preset partition fields of the nodes. The active power outputs of the power supplies connected to all nodes in the same partition and the node load are respectively arithmetically accumulated to generate the total power output value of the power supply of the equivalent regional node and the total equivalent load value, and the lines within the partition are deleted. The original connection lines between the equivalent nodes across partitions are retained as the simplified topology connection lines. Using the total power output value and the total equivalent load value as node data, a simplified power grid topology that retains the inter-regional connection relationship is formed. The partition field is a unique identifier representing the geographical or functional area to which the node belongs.

[0015] Further, the predicting the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system based on the source-load prediction program includes:

[0016] Determine the simulation duration and simulation time interval according to business requirements;

[0017] Input the simulation duration, simulation time interval, and original data into the source-load prediction program to obtain the output curves of wind and solar new energy and the load curve; wherein, the original data includes new energy output data, meteorological condition data, and historical output data.

[0018] Further, determining the upper and lower limits of the thermal power unit output constraints within the entire time zone according to the heating demand, includes:

[0019] Based on the typical curves of heat supply and power supply, construct the upper and lower limits of the thermal power unit output within the entire time interval;

[0020] Determine the upper and lower limits of the thermal power unit output constraints according to the active power output of the thermal power unit.

[0021] Further, constructing the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit, includes:

[0022] Determine the upper and lower limits of the hydropower unit output constraints according to the upper and lower limits of the hydropower unit output and the active power output of the hydropower unit;

[0023] Determine the power generation constraint conditions of the hydropower station according to the average value of the comprehensive power generation in different seasonal operation cycles and the total output of the hydropower unit.

[0024] Further, determining the charge-discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge-discharge power of the energy storage system, includes:

[0025] Determine the upper and lower limits of the charging power and the upper and lower limits of the discharging power of the energy storage system according to the charge-discharge power of the energy storage system;

[0026] Determine the charge-discharge power constraint conditions and the capacity constraint conditions according to the upper and lower limits of the charging power, the upper and lower limits of the discharging power, and the active power of the energy storage system.

[0027] Further, the multi-energy complementary power and electricity balance method considering the power grid topology further includes:

[0028] Construct the objective function of the optimization problem model according to the number of units, the number of lines, whether the units are started or stopped, the start-stop cost of the units, and the line transmission cost.

[0029] Further, solving the optimization problem model to obtain the dispatching strategy of the multi-energy complementary power system, includes:

[0030] An optimization algorithm is used to solve the optimization problem model to obtain a scheduling strategy for the multi - energy complementary power system. Among them, the optimization objective of the optimization algorithm is to minimize the sum of the unit start - stop cost and the line transmission cost, and the independent variables include the output curves of thermal power units, the output curves of hydropower units, and the output curves of energy storage systems.

[0031] The present invention also provides a multi - energy complementary power and electricity balance device considering the power grid topology, including:

[0032] A power grid topology simplification module, which is used to simplify the original power grid topology into a simplified power grid topology with regional interconnection according to the scale of the power grid, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads.

[0033] A power and electricity constraint condition construction module, which is used to predict the output curves of wind and solar new energy and the load curve of the multi - energy complementary power system based on a source - load prediction program, and determine the power and electricity constraint conditions required to be provided by non - new - energy units according to the output data in the output curves of wind and solar new energy and the load curve. Among them, the output data includes the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the output data of loads, the output data of wind turbines, and the output data of photovoltaic units.

[0034] A thermal power unit output upper and lower limit constraint condition construction module, which is used to determine the upper and lower limit constraint conditions of the thermal power unit output in the full - time zone according to the heating demand.

[0035] A power generation constraint condition construction module, which is used to construct the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit.

[0036] A charge - discharge power constraint condition construction module, which is used to determine the charge - discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge - discharge power of the energy storage system.

[0037] An optimization problem model construction module, which is used to establish an optimization problem model with the lowest sum of unit start - stop cost and line transmission cost as the objective based on the simplified power grid topology according to the power and electricity constraint conditions, the upper and lower limit constraint conditions of the thermal power unit output, the power generation constraint conditions, the charge - discharge power constraint conditions, and the capacity constraint conditions.

[0038] A power system scheduling module, which is used to solve the optimization problem model to obtain a scheduling strategy for the multi - energy complementary power system, and control the operating states of each unit of the power system according to the scheduling strategy to achieve power and electricity balance.

[0039] The present invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the multi-energy complementary power and electricity balance method considering the power grid topology as described above is implemented.

[0040] The present invention also provides a computer-readable storage medium, which includes a stored computer program; wherein, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the multi-energy complementary power and electricity balance method considering the power grid topology as described above.

[0041] By comprehensively considering the power and electricity constraint conditions, the upper and lower limit constraint conditions of the thermal power unit output, the power generation constraint conditions, the charge and discharge power constraint conditions, and the capacity constraint conditions, and on the basis of the simplified power grid topology obtained by simplification, the present invention establishes an optimization problem model with the goal of minimizing the sum of the unit start-stop cost and the line transmission cost, comprehensively considers multiple factors affecting the power and electricity balance, and considers the influence of the power grid topology information on the power and electricity balance effect, so that the optimal scheduling strategy can be obtained by solving the optimization problem model to guide the operation states of each unit (including thermal power, hydropower, wind power, solar energy, and energy storage) in the power system at different time periods to achieve the balance of power and electricity while minimizing the cost.

[0042] Furthermore, by accurately setting the simulation duration and time interval, the present invention can accurately simulate the operation of the power system, thereby improving the accuracy of the output and load prediction of new wind and solar energy; and by optimizing the power and electricity constraint conditions, it can effectively reduce unnecessary unit start-stops, reduce the operating cost, and further improve the reliability of the power and electricity balance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a schematic flowchart of the multi-energy complementary power and electricity balance method considering the power grid topology provided by an embodiment of the present invention;

[0044] Figure 2 is a schematic diagram of partition merging provided by an embodiment of the present invention;

[0045] Figure 3 is a schematic diagram of the upper and lower limit data of the output of each unit provided by an embodiment of the present invention;

[0046] Figure 4 is a schematic diagram of the output data of a hydropower plant provided by an embodiment of the present invention;

[0047] Figure 5 is a schematic diagram of a typical load curve provided by an embodiment of the present invention;

[0048] Figure 6It is a schematic diagram of a typical curve of photovoltaic power output provided by an embodiment of the present invention;

[0049] Figure 7 It is a schematic diagram of a typical curve of wind power output provided by an embodiment of the present invention;

[0050] Figure 8 It is a schematic diagram of the output curve of a wind power - thermal power unit provided by an embodiment of the present invention;

[0051] Figure 9 It is a schematic diagram of the output curve of a photovoltaic - hydropower unit provided by an embodiment of the present invention;

[0052] Figure 10 It is a schematic diagram of the output and energy curves of energy storage provided by an embodiment of the present invention;

[0053] Figure 11 It is a schematic diagram of the structure of a multi - energy complementary power and electricity balance device considering the power grid topology provided by an embodiment of the present invention. Specific embodiments

[0054] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0055] In the description of the present application, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "a plurality" is two or more.

[0056] In the description of the present application, it should be noted that unless otherwise clearly defined and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0057] Please refer to Figure 1, to solve the technical problem that completely ignoring the grid topology information in the prior art will lead to the imbalance between the balance calculation result and the actual situation, resulting in poor power and electricity balance effect, the present invention provides a multi - energy complementary power and electricity balance method considering the grid topology, including:

[0058] S1. According to the grid scale, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads, simplify the original grid topology into a simplified grid topology with regional interconnection;

[0059] In the embodiment of the present invention, by aggregating the power generation and load data of the grid nodes in the same region through the partition field and retaining the inter - regional tie lines, it is possible to significantly reduce the calculation complexity on the premise of ensuring the accuracy of power system analysis, while maintaining an accurate representation of the power interaction ability between regions.

[0060] S2. Based on the source - load prediction program, predict the output curves of wind and solar new energy and the load curve of the multi - energy complementary power system, and determine the power and electricity constraint conditions required to be provided by non - new energy units according to the output data in the output curves of wind and solar new energy and the load curve; where the output data includes the output data of thermal power units, hydropower units, energy storage systems, loads, wind turbine units, and photovoltaic units;

[0061] In the embodiment of the present invention, the source - load prediction program is a program used to predict the output curves of wind and solar new energy and the load curve according to the input data, where the input data may include the simulation duration, simulation time interval, new energy output data, meteorological condition data, and historical output data.

[0062] In the embodiment of the present invention, by predicting the output curves of wind and solar new energy and the load curve, it is possible to accurately determine the power and electricity constraint conditions required to be provided by non - new energy units according to the output data in the output curves of wind and solar new energy and the load curve, providing accurate data support for subsequent power and electricity balance.

[0063] S3. According to the heating demand, determine the upper and lower limit constraint conditions of the output of thermal power units in the full - time zone;

[0064] In the embodiment of the present invention, determining the upper and lower limits of the output of thermal power units according to the heating and power supply demands can ensure that while meeting the power demand, the thermal power units operate within a safe range, avoiding excessive fuel consumption or equipment overload.

[0065] S4. According to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of hydropower units, construct the power generation constraint conditions of the hydropower station;

[0066] S5. Determine the charge-discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge-discharge power of the energy storage system;

[0067] In the embodiment of the present invention, by determining the charge-discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge-discharge power of the energy storage system, the charge-discharge power and capacity limits of the energy storage system can be clarified, so as to reasonably plan the power generation plan of the hydropower station and improve the rationality of power and electricity balance.

[0068] S6. Based on the power and electricity constraint conditions, upper and lower limit constraint conditions of thermal power unit output, power generation constraint conditions, charge-discharge power constraint conditions and capacity constraint conditions, establish an optimization problem model with the lowest sum of unit start-stop costs and line transmission costs as the goal based on the simplified power grid topology;

[0069] S7. Solve the optimization problem model to obtain the scheduling strategy of the multi-energy complementary power system, and control the operating states of each unit of the power system according to the scheduling strategy to achieve power and electricity balance.

[0070] In the embodiment of the present invention, by comprehensively considering the power and electricity constraint conditions, upper and lower limit constraint conditions of thermal power unit output, power generation constraint conditions, charge-discharge power constraint conditions and capacity constraint conditions, an optimization problem model with the lowest sum of unit start-stop costs and line transmission costs as the goal is established, comprehensively considering multiple factors affecting power and electricity balance. Therefore, the optimal scheduling strategy can be obtained by solving the optimization problem model to guide the operating states of each unit (including thermal power, hydropower, wind power, solar energy and energy storage) in the power system at different time periods to achieve power and electricity balance while minimizing costs.

[0071] Please refer to Figure 3 , which is the data of the upper and lower limits of the output of each unit provided by the embodiment of the present invention.

[0072] In one embodiment, step S1. According to the scale of the power grid, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads, simplify the original power grid topology into a simplified power grid topology of regional interconnection, including:

[0073] S11. When the number of grid nodes is less than or equal to a preset threshold, the original grid topology is retained without aggregation processing; when the number of grid nodes is greater than the preset threshold, an aggregation operation is performed based on the preset partition field of the nodes. The active power outputs of the power supplies connected to all nodes within the same partition and the node loads are respectively arithmetically accumulated to generate the total power output value of the power supply of the equivalent regional node and the total equivalent load value, and the lines within the partition are deleted. The original connection lines between the equivalent nodes across partitions are retained as the simplified topology connection lines. Using the total power output value and the total equivalent load value as node data, a simplified grid topology that retains the inter-region connection relationship is formed. The partition field is a unique identifier representing the geographical or functional region to which the node belongs.

[0074] In the embodiment of the present invention, the preset threshold can be 100. For example, when the number of grid nodes exceeds 100, the grid needs to be aggregated according to partitions to simplify the topology.

[0075] In this embodiment, the definition of the original grid topology G is as follows:

[0076] G = (V, E, P, L);

[0077] Where:

[0078] V = {v1, v2, …, v n} is the node set (N = |V|);

[0079]

[0080] P: V → R + is the node active power output function;

[0081] L: V → R + is the node load function;

[0082] Among them, N is the number of grid nodes; partition attribute: define the belonging function v: V → ρ, where ρ = {1, 2, …, K} is the partition label set. Among them, π(v) = p means that node v belongs to partition p.

[0083] Threshold scale N0;

[0084] In this embodiment, the condition-triggered aggregation decision can be defined as:

[0085]

[0086] Among them, Ψ is the aggregation function based on partitions, and the definition is as shown in S12.

[0087] In the embodiment of the present invention, when aggregating the active power output and load of the nodes in the aggregation area, it is necessary to arithmetically accumulate the active power output and load of all nodes within the same area.

[0088] In this embodiment, the mathematical description of the partition aggregation operation Ψ(G) is as follows:

[0089] Partition the nodes according to their attributes:

[0090]

[0091] Among them, represents the set of partition labels, and V p represents the set of all nodes belonging to partition p, and π(v) = p means that node v belongs to partition p.

[0092] After partitioning, it satisfies:

[0093]

[0094] Among them, K is the number of elements in the node label set, V p represents the set of all nodes belonging to partition p, and V q represents the set of all nodes belonging to partition q.

[0095] Equivalent parameter calculation:

[0096] · Equivalent output

[0097]

[0098] Among them, is the total output of all nodes within partition p.

[0099] · Equivalent load:

[0100]

[0101] Among them represents the i-th node in partition p.

[0102] Topology simplification:

[0103] · Remove the edges within the partition to simplify the topology, and only retain the inter-region interconnection relationships:

[0104]

[0105] Among them, E intra is the edge within the partition, is the total load of all nodes within partition p.

[0106] · Retain the cross-region edges and project:

[0107]

[0108] Among them, To retain the edge set after cross-region partitioning, (u, v) represents the edge between node u and node v.

[0109] · Line parameter inheritance, that is, the parameters of the original cross-region line are retained in the new simplified line.

[0110] When (u, v) ∈ E and π(u) = p, π(v) = q;

[0111] Among them, Z pq represents the parameter of the edge between partition p and partition q, and Z uv represents the parameter of the edge between node u and node v.

[0112] The simplified power grid topology is as follows:

[0113]

[0114] Among them:

[0115]

[0116] Among them, represents the simplified node set, and represents the simplified equivalent output and load function, directly inherited from the sum of the partitions.

[0117] In one embodiment, in step S2, based on the source-load prediction program, the output curves and load curves of the wind and solar new energy in the multi-energy complementary power system are predicted, including:

[0118] S21. Determine the simulation duration and simulation time interval according to the service requirements;

[0119] In the embodiments of the present invention, the simulation duration determines the duration of the simulation, and the simulation time interval determines the accuracy of the simulation. In actual power system simulations, it is necessary to determine the appropriate simulation duration and simulation time interval according to the research purpose, available computing resources, and requirements for data accuracy. For example, the simulation duration can be determined according to the service requirements. When the service is to formulate an annual power generation plan, the simulation duration is taken as a year; when formulating a monthly power generation plan, the simulation duration is taken as a month. The simulation time interval can be one hour, 15 minutes, 10 minutes, etc.

[0120] In the embodiments of the present invention, the simulation duration T can be expressed as:

[0121] t ∈ T 集合 = {0, Δt, 2Δt, 3Δt,..., T} (1)

[0122] Among them, T is the simulation duration, and Δt is the simulation time interval.

[0123] S22. Input the simulation duration, simulation time interval, and original data into the source-load prediction program to obtain the output curves of wind and solar new energy and the load curve. Among them, the original data includes new energy output data, meteorological condition data, and historical output data.

[0124] In the embodiment of the present invention, the output curve of wind and solar new energy is the variation of the power generation of the system over a period of time. The shape of the output curve of wind and solar new energy is affected by seasons and meteorological conditions. The load curve refers to the variation of the power consumption of a certain area or user in the power system over a certain period of time, usually manifested as the power demand in different time periods within a certain time.

[0125] The embodiment of the present invention can input the simulation duration, simulation time interval, and original data into the source-load prediction program to construct the output curves of wind and solar new energy and the load curve. Among them, the length of the horizontal axis of these two curves is the full length of the simulation time, the number of points on the curve is the full length of time / time interval, and the vertical axis of the curve is the active power at a certain time t.

[0126] In the embodiment of the present invention, the power and electricity quantity constraint conditions required by non-new energy units can be:

[0127]

[0128] Among them, P 火,t 、P 水,t 、P 储,t 、P 荷,t 、P 风,t 、P 光,t are the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the active power data of loads, the output data of wind turbines, and the output data of photovoltaic units at time t, respectively.

[0129] In one embodiment, step S3. Determine the upper and lower limit constraint conditions of the output of thermal power units in the full time zone according to the heating demand, including:

[0130] S31. Based on the typical curve of heat supply and power supply, construct the upper and lower limits of the output of thermal power units in the full time interval;

[0131] S32. Determine the upper and lower limit constraint conditions of the output of thermal power units according to the active output of thermal power units.

[0132] In the embodiment of the present invention, since some units undertake both heating and power supply tasks, their lower output limits are restricted by the heating demand and they must supply power on the premise of ensuring heating. At the same time, considering the static parameters of the units, the upper output limits of the units are also physically restricted. These factors together determine the upper and lower limit constraint conditions of the output of the units in each time period. The upper and lower limit constraint conditions of the output of thermal power units are:

[0133]

[0134] Among them, P 火,max and P 火,min respectively represent the upper and lower limits of the output of the thermal power unit, and P 火,t represents the active power output of the thermal power unit at time t.

[0135] In one embodiment, step S4: Construct the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit, including:

[0136] S41: Determine the upper and lower limit constraint conditions of the output of the hydropower unit according to the upper and lower limits of the output of the hydropower unit and the active power output of the hydropower unit;

[0137] Please refer to Figure 4 , which is a schematic diagram of the output data of the hydropower plant provided by the embodiment of the present invention. In the embodiment of the present invention, the seasonal operation cycle includes the flood season, the normal water season, and the dry season, and the maximum output, minimum output, and average output of the hydropower plant in different historical periods can be constructed. The output of the hydropower plant during the simulation process does not exceed the historical maximum value of each period and is not lower than the historical minimum value; the historical power generation is calculated by multiplying the average value of the total power generation in each historical period by the total length of the simulation time, and the power generation is solved according to the average output curve.

[0138] In the embodiment of the present invention, the upper and lower limit constraint conditions of the output of the hydropower unit can be:

[0139]

[0140] Among them, P 水,max and P 水,min respectively represent the upper and lower limits of the output of the hydropower unit, and P 水,t represents the active power output of the hydropower unit at time t.

[0141] S42: Determine the power generation constraint conditions of the hydropower station according to the average value of the comprehensive power generation in different seasonal operation cycles and the total output of the hydropower unit.

[0142] In the embodiment of the present invention, the power generation constraint conditions of the hydropower station are:

[0143] ∑P 水,t *Δt = P 水,avg *T (5)

[0144] Among them, P 水,avg refers to the average value of the comprehensive power generation in each historical period, and ∑P 水,tIt refers to the sum of the outputs of the hydropower unit at all time points from 0 to T. The meaning expressed by formula (5) is that the electricity generated at the current stage from 0 to time T should be consistent with the historical average power generation.

[0145] In one embodiment, step S5: Determine the charge-discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge-discharge power of the energy storage system, including:

[0146] S51: Determine the upper and lower limits of the charging power and the upper and lower limits of the discharging power of the energy storage system according to the charge-discharge power of the energy storage system;

[0147] In the embodiment of the present invention, the role of the energy storage system in the new energy system is to balance the source-load fluctuations. For example, when the new energy output is excessive, the excess electric energy is stored; when the new energy output is insufficient, the energy storage system releases the stored electric energy to maintain the power supply and ensure the stable operation of the system. The upper and lower limits of the electric quantity of the energy storage system and the charge-discharge power constraint are restricted by the physical characteristics of the energy storage device. Its energy storage capacity is limited and it cannot store electric energy infinitely. At the same time, its charge-discharge power is also limited, and its input and output power cannot exceed the physical property limit of the device.

[0148] S52: Determine the charge-discharge power constraint conditions and capacity constraint conditions according to the upper and lower limits of the charging power, the upper and lower limits of the discharging power, and the active power of the energy storage system.

[0149] In the embodiment of the present invention, the charge-discharge power constraint conditions can be:

[0150] P 储,充,min ≤P 储,充,t ≤P 储,充,max (6)

[0151] P 储,放,min ≤P 储,放,t ≤P 储,放,max

[0152] The above formula satisfies:

[0153] Wherein, P 储,充,max 、P 储,充,min respectively represent the upper and lower limits of the charging power of the energy storage, and P 储,放,max 、P 储,放,min respectively represent the upper and lower limits of the discharging power of the energy storage, and P 储,t represents the active power output of the energy storage at time t.

[0154] The capacity constraint conditions can be:

[0155] 0≤∑P 储,充 / 放,t *Δt≤S (7)

[0156] Wherein, ∑P储,t It refers to the sum of the outputs of the energy storage system at all time points from 0 to T. S represents the upper limit of the capacity of the energy storage system.

[0157] In one embodiment, the multi - energy complementary power and electricity balance method considering the power grid topology further includes:

[0158] Construct the objective function of the optimization problem model according to the number of units, the number of lines, whether the units start or stop, the start - stop cost of the units, and the line transmission cost.

[0159] In the embodiment of the present invention, the expression of the objective function can be as follows:

[0160]

[0161] G i ∈G 集合 ={0, 1}

[0162] Among them, n is the number of units, m is the number of lines, G i represents whether the i - th unit starts or stops, C i is the start - stop cost of the i - th unit, L k is the k - th line, E k is the transmission cost of the k - th line. When the i - th unit starts or stops, G i =1; when the i - th unit has no start - stop action, G i =0.

[0163] The expression of the optimization problem model based on the above - mentioned objective function is as follows:

[0164]

[0165] In one embodiment, step S6, solve the optimization problem model to obtain the scheduling strategy of the multi - energy complementary power system, including:

[0166] Use an optimization algorithm to solve the optimization problem model to obtain the scheduling strategy of the multi - energy complementary power system; among them, the optimization goal of the optimization algorithm is to minimize the sum of the unit start - stop cost and the line transmission cost, and the independent variables include the output curves of thermal power units, hydropower units, and the output curve of the energy storage system.

[0167] In this embodiment, an optimization problem model obtained by using a genetic algorithm for solution. In the genetic algorithm of the embodiment of the present invention, a fitness function is used to evaluate the quality of an individual or a solution. According to the mapping relationship between the objective function and the individual fitness, selection of the fittest is carried out according to the level of the fitness value. Gene expression converts the independent variables (i.e., algorithm parameters and individual genotypes) in the genetic algorithm into dependent variables (i.e., inputs of the fitness function) that can be evaluated in the problem space. Through gene expression, the genetic algorithm can convert the chromosome encoding of an individual into an actual solution and evaluate it in the problem space, so as to determine its fitness. A penalty function is used to handle the constraint conditions in the genetic algorithm. When the gene expression of an individual violates the problem constraints, the penalty function will reduce its fitness value, thereby reducing the survival probability of infeasible solutions in the selection. The role of the penalty function is to transform the constrained optimization problem into an unconstrained problem while ensuring that all constraint conditions are met.

[0168] In the embodiment of the present invention, when solving the optimization problem of minimizing the sum of the unit start-stop cost and the line transmission cost, the goal of the fitness function is to minimize the sum of the unit start-stop cost and the line transmission cost. The independent variables include the output curves of thermal power units, hydropower units, and energy storage systems. The penalty function is used to handle the constraint conditions, including the system grid structure, source-load prediction results, upper and lower limits of thermal power unit output, hydropower plant output, energy storage charge-discharge power, and upper and lower limits of electricity quantity.

[0169] The embodiment of the present invention uses a genetic algorithm to solve the optimization problem with the goal of minimizing the sum of the unit start-stop cost and the line transmission cost, achieving an optimized dispatching strategy. Based on this optimized dispatching strategy, it is possible to guide the operating states of various units (including thermal power, hydropower, wind power, solar energy, and energy storage) in the power system at different time periods to achieve the balance of power and electricity, while minimizing the cost.

[0170] In one embodiment, an energy and power balance method considering power grid topology in the embodiment of the present invention is applied to a certain multi-energy complementary power system, including:

[0171] S10. Considering the number of nodes in the power grid, if it exceeds a certain scale, then the power grid is aggregated to simplify the topology.

[0172] Please refer to Figure 2 , which is a graph of the active power output of the nodes in the aggregated power grid area.

[0173] Before the data in the figure is merged, there are a total of five nodes, namely:

[0174] GD1, partition GD, active power output 100MW, load 50MW;

[0175] GD2, partition GD, active power output 300MW, load 250MW;

[0176] GD3, GD sub - region, active power output is 200 MW, load is 175 MW;

[0177] YN1, YN sub - region, active power output is 100 MW, load is 125 MW;

[0178] YN2, YN sub - region, active power output is 150 MW, load is 250 MW.

[0179] The tie - lines among them are:

[0180] GD1 -> GD2 (within the sub - region), impedance is 0.09;

[0181] GD1 -> YN1 (across sub - regions), impedance is 0.05;

[0182] GD1 -> GD3 (within the sub - region), impedance is 0.06;

[0183] GD2 -> YN2 (across sub - regions), impedance is 0.08.

[0184] According to the above - mentioned simplification process, the simplification steps are as follows:

[0185] Sub - region division:

[0186] According to the sub - region label π(v), the nodes are divided into two mutually exclusive subsets:

[0187] V GD = {GD1, GD2, GD3};

[0188] V YN = {YN1, YN2};

[0189] Verify coverage and mutual exclusivity:

[0190]

[0191] Equivalent parameter calculation

[0192] 1. Equivalent active power output:

[0193]

[0194] 2. Equivalent load:

[0195]

[0196] Topological simplification:

[0197] 1. Remove the edges within the sub - region:

[0198] E intra = {GD1 → GD2, GD1 → GD3};

[0199] 2. Retain cross - regional edges and map:

[0200]

[0201] Original cross - regional edge mapping relationship:

[0202]

[0203] Line parameter inheritance:

[0204] The original cross - regional line parameters are:

[0205] GD1→YN1: Impedance 0.05 p.u.

[0206] GD2→YN2: Impedance 0.08 p.u. Then the equivalent line parameters are:

[0207]

[0208] Simplify the power grid topology:

[0209]

[0210] Equivalent nodes:

[0211]

[0212] Equivalent edges:

[0213]

[0214] Equivalent parameters:

[0215]

[0216] According to the above steps, the merged result is:

[0217] Region GD, active power output is 600 MW, load is 475 MW;

[0218] Region YN, active power output is 250 MW, load is: 375 MW;

[0219] Data of the inter - regional tie line:

[0220]

[0221] S20. Determine that the simulation duration is 24 hours, the simulation time interval is 1 hour, and there are 24 time periods. In this embodiment, the power - electricity balance method of the multi - energy complementary power system is used to simulate the 4 - machine 6 - node system.

[0222] The 24-hour simulation can cover all periods within a day of the power system, including peak, trough, and transitional periods, so as to analyze the daily load variation, power generation scheduling, and reserve demand of the system. For new energy power generation such as wind power and photovoltaic power, their output is intermittent and uncertain. The 24-hour simulation can analyze the output characteristics of these new energy sources at different time periods, evaluate their impact on the system, and explore integration strategies. The simulation with a time interval of 1 hour can control the calculation amount within a reasonable range while ensuring the simulation accuracy. This setting can ensure the reliability of the simulation results and avoid excessive computational burden.

[0223] S30. Based on past load data, the source-load prediction program constructs Figure 5 the typical load curve as shown, and obtains the typical load curve for the entire time period. The active load is normalized and converted for the given data according to its proportion in the system. The specific method is: multiplying the load at each point by the reference load and then dividing by the average hourly load to obtain the normalized and converted load.

[0224] Please refer to Table 1 for the predicted load values for each time period. Among them, Node 1, Node 2, Node 3, Node 4, and Node 5 are load nodes.

[0225] Table 1: Predicted Load Values for Each Time Period

[0226]

[0227] In the embodiment of the present invention, based on the past output of wind and solar new energy sources, the source-load prediction program constructs a typical output curve of wind and solar new energy sources, and obtains the typical output curve of wind and solar new energy sources for the entire time period. The output of new energy units is normalized and converted for the given data according to its proportion in the system. The specific method is: multiplying the power generation at each point by the reference power generation and then dividing by the average hourly power generation to obtain the normalized and converted load.

[0228] Please refer to Figures 6 - 7 , and the embodiment of the present invention can also construct a typical curve of photovoltaic output and a typical curve of wind power output.

[0229] Please refer to Table 2 for the predicted output values of new energy sources.

[0230] Table 2: Predicted Output Values of New Energy Sources

[0231]

[0232] S40. Considering the heating and power supply demands, construct the upper and lower limits of the output of thermal power units within the entire time interval. The upper limit of the output of thermal power units is 100 MW, and the lower limit is 0. The upper and lower limits of the output of each unit are as Figures 8 - 10As shown, the upper limit of the output of the photovoltaic unit is 25,000 MW, the upper limit of the output of the wind turbine unit is 1,200 MW, and the upper limit of the output of the hydropower unit is 2,000 MW.

[0233] S50. According to the past power generation data of the hydropower plant, considering the wet season, normal season, and dry season, construct the maximum output, minimum output, and average output of the hydropower plant, as Figure 6 shown. Set the simulation environment as a normal year. Based on the past power generation data of the hydropower plant, the maximum output of the hydropower plant in this embodiment is 50 WM, the minimum output is 0, and the average output is 25 MW.

[0234] S60. Considering the charging and discharging power of the energy storage, construct the maximum and minimum power constraints of the energy storage. Set the upper limit of the energy storage capacity to 300 MW, the charging power of the energy storage to: 225 MW, and the discharging power of the energy storage to: 237 MW.

[0235] S70. According to the above constraints, establish an optimization problem model with the goal of minimizing the sum of the unit start-stop cost and the line transmission cost; in this embodiment, the start-stop cost C of all units is 60,000 yuan, and all line transmission costs are 0.05 yuan / kWh.

[0236]

[0237] S80. Use an optimization algorithm to solve the optimization problem model to obtain the optimal solution.

[0238] Implementing the embodiment of the present invention has the following beneficial effects:

[0239] In the embodiment of the present invention, by comprehensively considering the power and energy constraints, the upper and lower limits of the output of thermal power units, the power generation constraints, the charging and discharging power constraints, and the capacity constraints, and on the basis of the simplified power grid topology obtained by simplification, an optimization problem model with the goal of minimizing the sum of the unit start-stop cost and the line transmission cost is established, comprehensively considering multiple factors affecting the power and energy balance, and considering the influence of the power grid topology information on the power and energy balance effect, so that the optimal scheduling strategy can be obtained by solving the optimization problem model to guide the operation states of each unit (including thermal power, hydropower, wind power, solar energy, and energy storage) in the power system at different time periods to achieve the balance of power and energy while minimizing the cost.

[0240] Furthermore, in the embodiment of the present invention, by accurately setting the simulation duration and time interval, the operation of the power system can be accurately simulated, thereby improving the accuracy of the output and load prediction of new wind and solar energy; and by optimizing the power and energy constraints, unnecessary unit start-stops can be effectively reduced, the operation cost can be reduced, and further the reliability of the power and energy balance can be improved.

[0241] Please refer to Figure 11, based on the same inventive concept as the above embodiments, the present invention also provides a multi-energy complementary power and electricity balance device considering the power grid topology, including:

[0242] A power grid topology simplification module 10, configured to simplify the original power grid topology into a simplified power grid topology with regional interconnection according to the power grid scale, as well as the active power output of the power sources connected to all nodes within the same partition and the node loads.

[0243] A power and electricity constraint condition construction module 20, configured to predict the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system based on a source-load prediction program, and determine the power and electricity constraint conditions required to be provided by non-new energy units according to the output data in the output curves of wind and solar new energy and the load curve; wherein the output data includes the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the output data of loads, the output data of wind turbines, and the output data of photovoltaic units.

[0244] A thermal power unit output upper and lower limit constraint condition construction module 30, configured to determine the upper and lower limit constraint conditions of the thermal power unit output within the entire time zone according to the heating demand.

[0245] A power generation constraint condition construction module 40, configured to construct the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit.

[0246] A charge and discharge power constraint condition construction module 50, configured to determine the charge and discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge and discharge power of the energy storage system.

[0247] An optimization problem model construction module 60, configured to establish an optimization problem model with the lowest total of unit start-stop costs and line transmission costs as the goal based on the simplified power grid topology according to the power and electricity constraint conditions, the thermal power unit output upper and lower limit constraint conditions, the power generation constraint conditions, the charge and discharge power constraint conditions, and the capacity constraint conditions.

[0248] A power system dispatching module 70, configured to solve the optimization problem model, obtain the dispatching strategy of the multi-energy complementary power system, and control the operating states of the various units of the power system according to the dispatching strategy to achieve power and electricity balance.

[0249] In one embodiment, the power grid topology simplification module 10 is also used to: when the number of power grid nodes is less than or equal to a preset threshold, retain the original power grid topology without aggregation processing; when the number of power grid nodes is greater than the preset threshold, perform aggregation operations based on the node preset partition field, and perform arithmetically accumulation on the active power output and node load of the power sources connected to all nodes in the same partition, generate the total power output and the total equivalent load of the equivalent regional nodes, delete the lines within the partition, retain the original connecting lines between the equivalent nodes across the partition as simplified topology connection lines, use the total power output and the total equivalent load as node data, and form a simplified power grid topology that retains the interconnection relationship between regions, and the partition field is a unique identifier that represents the geographical or functional area to which the node belongs.

[0250] In one embodiment, the power quantity constraint condition building module 20 is further configured to:

[0251] Determine the simulation duration and simulation time interval based on business requirements;

[0252] The simulation duration, simulation time interval and original data are input into the source-load prediction program to obtain the wind and solar energy output curve and load curve; among them, the original data includes new energy output data, meteorological condition data and historical output data.

[0253] In one embodiment, the thermal power unit output upper and lower limit constraint condition construction module 30 is further used to:

[0254] Based on the typical curve of heat and power supply, the upper and lower limits of thermal power unit output in the whole time interval are established;

[0255] According to the active power output of the thermal power unit, the upper and lower limit constraints of the thermal power unit output are determined.

[0256] In one embodiment, the power generation constraint condition building module 40 is further configured to:

[0257] Determine the upper and lower output constraints of the hydropower unit based on its output upper and lower limits and its active power output;

[0258] The power generation constraints of the hydropower station are determined based on the average comprehensive power generation of different seasonal operation cycles and the total output of the hydropower units.

[0259] In one embodiment, the charge and discharge power constraint condition building module 50 is further configured to:

[0260] Determine the upper and lower limits of the energy storage system's charging and discharging power based on the system's charging and discharging power;

[0261] The charging and discharging power constraints and capacity constraints are determined based on the upper and lower limits of charging power, the upper and lower limits of discharging power, and the active power of the energy storage system.

[0262] In one embodiment, the device further includes an objective function construction module, configured to:

[0263] Construct an objective function of the optimization problem model according to the number of units, the number of lines, whether the units are started or stopped, the unit start-stop cost, and the line transmission cost.

[0264] In one embodiment, the power system scheduling module 70 is further configured to:

[0265] Solve the optimization problem model by using an optimization algorithm to obtain a scheduling strategy for the multi-energy complementary power system; wherein, the optimization objective of the optimization algorithm is to minimize the sum of the unit start-stop cost and the line transmission cost, and the independent variables include the output curves of thermal power units, the output curves of hydropower units, and the output curves of energy storage systems.

[0266] Correspondingly, an embodiment of the present invention further provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the multi-energy complementary power and electricity balance method considering the power grid topology in any one of the above embodiments is implemented.

[0267] The terminal device of this embodiment includes: a processor, a memory, and a computer program and computer instructions stored in the memory and executable on the processor. When the processor executes the computer program, the respective steps in the first embodiment above are implemented, such as Figure 1 The steps S1 to S7 shown. Alternatively, when the processor executes the computer program, the functions of each module / unit in the above device embodiment are implemented, such as the optimization problem model construction module 60.

[0268] Exemplarily, the computer program may be divided into one or more modules / units. One or more modules / units are stored in the memory and executed by the processor to complete the present invention. One or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device. For example, the optimization problem model construction module 60 is configured to establish an optimization problem model with the lowest sum of the unit start-stop cost and the line transmission cost as the objective according to the power and electricity constraint conditions, the upper and lower limit constraint conditions of the output of thermal power units, the power generation constraint conditions, the charge and discharge power constraint conditions, and the capacity constraint conditions.

[0269] The terminal device can be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the schematic diagram is only an example of the terminal device and does not constitute a limitation on the terminal device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, a bus, etc.

[0270] The so-called processor may be a central processing unit (CPU), or may 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 gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the terminal device and connects various parts of the entire terminal device through various interfaces and lines.

[0271] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. Among them, the program storage area may store an operating system, application programs required for at least one function, etc.; the data storage area may store data created according to the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory and may also include non-volatile memory, such as 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 magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0272] Among them, if the modules / units integrated in the terminal device 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. Based on such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can 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, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice within the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0273] Correspondingly, an embodiment of the present invention further provides a computer-readable storage medium. The computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the multi-energy complementary power and electricity balance method considering the power grid topology in any one of the above embodiments.

[0274] The above specific embodiments further elaborate on the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not used to limit the protection scope of the present invention. It is particularly pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A multi - energy complementary power and electricity balance method considering power grid topology, characterized in that Including: Simplify the original power grid topology into a simplified power grid topology with regional interconnections according to the scale of the power grid, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads. Based on the source-load prediction program, predict the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system, and determine the power and electricity quantity constraint conditions required to be provided by non-new energy units according to the output data in the output curves of wind and solar new energy and the load curve; wherein, the output data includes the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the output data of loads, the output data of wind turbines, and the output data of photovoltaic units. Determine the upper and lower limit constraint conditions of the output of thermal power units in the entire time zone according to the heating demand. Construct the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit. Determine the charge-discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge-discharge power of the energy storage system. Based on the power and electricity quantity constraint conditions, the upper and lower limit constraint conditions of the output of thermal power units, the power generation constraint conditions, the charge-discharge power constraint conditions, and the capacity constraint conditions, establish an optimization problem model with the lowest total of unit start-stop costs and line transmission costs as the goal based on the simplified power grid topology. Solve the optimization problem model to obtain the dispatching strategy of the multi-energy complementary power system, and control the operating states of each unit of the power system according to the dispatching strategy to achieve power and electricity balance.

2. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, characterized in that, The step of simplifying the original power grid topology into a simplified power grid topology with regional interconnections according to the scale of the power grid, as well as the active power output of the power sources connected to all nodes in the same partition and the node loads, includes: When the number of power grid nodes is less than or equal to the preset threshold, retain the original power grid topology without aggregation processing; when the number of power grid nodes is greater than the preset threshold, perform an aggregation operation based on the preset partition field of the nodes, arithmetically accumulate the active power output of the power sources connected to all nodes in the same partition and the node loads respectively, generate the total power output value of the power source of the equivalent regional node and the total equivalent load value, delete the lines within the partition, retain the original connection lines between the equivalent nodes across partitions as the simplified topology connection lines, and use the total power output value and the total equivalent load value as node data to form a simplified power grid topology that retains the interconnection relationship between regions, where the partition field is a unique identifier representing the geographical or functional area to which the node belongs.

3. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, characterized in that The step of predicting the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system based on the source-load prediction program includes: Determine the simulation duration and simulation time interval according to the service requirements. Input the simulation duration, simulation time interval, and original data into the source-load prediction program to obtain the output curves of wind and solar new energy and the load curve; wherein, the original data includes new energy output data, meteorological condition data, and historical output data.

4. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, characterized in that, The step of determining the upper and lower limit constraint conditions of the output of thermal power units in the entire time zone according to the heating demand includes: Based on the typical curves of heat supply and power supply, construct the upper and lower limits of the output of thermal power units within the entire time interval; According to the active power output of thermal power units, determine the constraint conditions for the upper and lower limits of the output of the thermal power units.

5. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, wherein, According to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit, construct the power generation constraint conditions of the hydropower station, including: According to the upper and lower limits of the output of the hydropower unit and the active power output of the hydropower unit, determine the constraint conditions for the upper and lower limits of the output of the hydropower unit; According to the average value of the comprehensive power generation in different seasonal operation cycles and the total output of the hydropower unit, determine the power generation constraint conditions of the hydropower station.

6. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, characterized in that According to the charge and discharge power of the energy storage system, determine the charge and discharge power constraint conditions and capacity constraint conditions of the energy storage system, including: According to the charge and discharge power of the energy storage system, determine the upper and lower limits of the charging power and the upper and lower limits of the discharging power of the energy storage system; According to the upper and lower limits of the charging power, the upper and lower limits of the discharging power and the active power of the energy storage system, determine the charge and discharge power constraint conditions and the capacity constraint conditions.

7. The multi-energy complementary power and electricity balance method considering the power grid topology according to claim 1, characterized in that It also includes: Based on the number of units, the number of lines, whether the units are started or stopped, the start-stop cost of the units and the line transmission cost, construct the objective function of the optimization problem model.

8. The multi-energy complementary power and electricity balance method considering power grid topology according to claim 1, characterized in that Solving the optimization problem model to obtain the scheduling strategy of the multi-energy complementary power system, including: Using an optimization algorithm to solve the optimization problem model to obtain the scheduling strategy of the multi-energy complementary power system; among them, the optimization goal of the optimization algorithm is to minimize the sum of the start-stop cost of the units and the line transmission cost, and the independent variables include the output curve of the thermal power unit, the output curve of the hydropower unit and the output curve of the energy storage system.

9. A multi-energy complementary power and electricity balance device considering power grid topology, characterized in that It includes: A grid topology simplification module, which is used to simplify the original grid topology into a simplified grid topology with regional interconnection according to the grid scale, as well as the active power output of the power sources connected to all nodes in the same partition and the node load; A power and electricity constraint condition construction module, which is used to predict the output curves of wind and solar new energy and the load curve of the multi-energy complementary power system based on a source-load prediction program, and determine the power and electricity constraint conditions required to be provided by non-new energy units according to the output data in the output curves of wind and solar new energy and the load curve; among them, the output data includes the output data of thermal power units, the output data of hydropower units, the output data of energy storage systems, the output data of loads, the output data of wind turbines and the output data of photovoltaic units; A thermal power unit output upper and lower limit constraint condition construction module, which is used to determine the constraint conditions for the upper and lower limits of the output of thermal power units within the entire time zone according to the heating demand; A power generation constraint condition construction module, which is used to construct the power generation constraint conditions of the hydropower station according to the seasonal operation cycle of the hydropower station, as well as the lower limit and upper limit of the output of the hydropower unit; A charge and discharge power constraint condition construction module, which is used to determine the charge and discharge power constraint conditions and capacity constraint conditions of the energy storage system according to the charge and discharge power of the energy storage system; An optimization problem model construction module, configured to establish an optimization problem model with the lowest sum of unit start-stop costs and line transmission costs as the objective based on the simplified power grid topology according to the power and electricity quantity constraint conditions, the upper and lower limits of thermal power unit output constraint conditions, the power generation constraint conditions, the charge and discharge power constraint conditions, and the capacity constraint conditions; A power system scheduling module, configured to solve the optimization problem model to obtain a scheduling strategy for the multi-energy complementary power system, and control the operating states of the various units of the power system according to the scheduling strategy to achieve power and electricity quantity balance.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program; wherein, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the multi-energy complementary power and electricity quantity balance method considering the power grid topology according to any one of claims 1-8.

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