New energy consumption capability evaluation method and device considering power demand response, equipment and medium

Abstract

The invention discloses a new energy consumption capability evaluation method and device considering power demand response, equipment and a medium, and the method comprises the steps: obtaining the related data of a power system; establishing a power model of wind power, photovoltaic power generation and load, and generating power data of wind power, photovoltaic power generation and load in a future time period; establishing a power demand response model which comprises a price type demand response model and an excitation type demand response model; establishing a new energy consumption capability evaluation model considering the power demand response; and calculating to obtain a new energy consumption capability evaluation result considering the power demand response through an optimization solution method. According to the method, the influence of the power demand response on the new energy consumption capability is fully considered, the new energy consumption capability considering the power demand response can be accurately evaluated, decision support is provided for an energy competent department to scientifically make power demand response related policies, a basis is provided for reasonable planning and differentiated access strategies of wind power and photovoltaic power generation, and the new energy consumption capability can be accurately evaluated. And a foundation is laid for optimizing a transaction strategy by the electricity market participant.

Description

Technical Field

[0001] The present invention belongs to the field of renewable energy power generation technology, and specifically relates to a method, device, equipment and medium for evaluating renewable energy absorption capacity taking into account power demand response. Background Art

[0002] As the energy transition continues to deepen, the power system's power source structure is evolving from a dominance of deterministic, adjustable, and controllable conventional power sources to a dominance of random, intermittent, and fluctuating renewable energy generation, ultimately leading to a dominance of renewable energy power generation. It is projected that by 2060, my country's installed renewable energy capacity and power generation will account for 64.6% and 58.6%, respectively. The output characteristics of renewable energy, such as randomness, volatility, and anti-peaking properties, are increasingly impacting the system's power and electricity balance. Currently, curtailment of renewable energy generation due to insufficient power system capacity to absorb renewable energy has become a common phenomenon. Data released by the National New Energy Absorption Monitoring and Early Warning Center shows that in 2024, the national photovoltaic power generation utilization rate will be 96.8%, and the wind power utilization rate will be 95.9%.

[0003] The "Electricity Demand Side Management Measures (2023 Edition)" explicitly mandates that by 2025, each province's demand response capability reach 3%-5% of its maximum electricity load, with provinces experiencing annual peak-to-valley variations exceeding 40% reaching 5% or higher. By 2030, a large-scale, real-time demand response capability will be established, and combined with ancillary service markets and electricity energy market transactions, demand-side resource sharing and mutual assistance within the power grid region will be achieved. Because electricity demand response is primarily a measure that uses economic incentives to guide electricity users to voluntarily adjust their electricity consumption based on the needs of power system operations, achieving peak shaving and valley filling, and improving power system flexibility, it is an important measure to promote the absorption of new energy power. Therefore, how to scientifically and quantitatively evaluate the absorption capacity of new energy sources that takes electricity demand response into account has become an important research direction. Summary of the Invention

[0004] In response to the deficiencies of the prior art, the present invention provides a method, device, equipment and medium for evaluating the new energy absorption capacity taking into account the power demand response.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for evaluating new energy consumption capacity taking into account power demand response, comprising the following steps:

[0007] Step S1: Acquire power system related data, wherein the power system related data includes wind power data, photovoltaic power generation data and load data;

[0008] Step S2: Based on the wind power data, photovoltaic power generation data and load data obtained in step S1, a power model of wind power, photovoltaic power generation and load is established to generate power data of wind power, photovoltaic power generation and load in the future period;

[0009] Step S3: Establishing an electricity demand response model, including a price-based demand response model and an incentive-based demand response model;

[0010] Step S4: Establish a new energy consumption capacity assessment model, and add the power demand response model established in step S3 as a control method and constraint condition to the new energy consumption capacity assessment model to form a new energy consumption capacity assessment model that takes power demand response into account;

[0011] Step S5: Using the power system related data obtained in step S1 and the power data of wind power, photovoltaic power generation and load in the future period obtained in step S2 as input data, the new energy absorption capacity assessment model considering power demand response established in step S4 is calculated through the optimization solution method to obtain the new energy absorption capacity assessment result considering power demand response.

[0012] Furthermore, in step S1, the wind power data includes historical power data of wind power and future installed capacity development data, the photovoltaic power generation data includes historical power data of photovoltaic power generation and future installed capacity development data, the load data includes historical power data of load and future demand development data, and the power system-related data also includes electricity price data, spare capacity data, transmission section data, energy storage data, conventional unit data, etc.

[0013] Furthermore, in step S2, the power models of wind power, photovoltaic power generation, and load established include a basic model and a development model. The basic model first identifies the dynamic characteristics of source and load resources by evaluating and analyzing historical power data of wind power, photovoltaic power generation, and load at multiple time scales and dimensions, and determines the short-term periodic characteristics, long-term seasonal characteristics, and capacity change characteristics of the source and load resources; then, through production simulation technology, the power data of wind power, photovoltaic power generation, and load in the new energy absorption capacity assessment cycle that meets the relevant characteristic indicators is obtained;

[0014] Based on the basic models of wind power, photovoltaic power generation, and load, the impact of the development of wind power and photovoltaic power generation installed capacity and load demand on their power during the assessment period is considered, and a development model of wind power, photovoltaic power generation, and load that takes into account capacity / demand development is established. The calculation formula is as follows:

[0015]

[0016] In the formula, type represents type. When type is w, it represents wind power, when type is s, it represents photovoltaic power generation, and when type is ld, it represents load. Indicates the historical installed capacity or load demand of wind power / photovoltaic power generation; The wind power / photovoltaic power generation installed capacity or load demand at time t is considered to take into account the development of wind power / photovoltaic power generation installed capacity and load demand; represents the wind power / photovoltaic power generation installed capacity or load demand at the initial moment of the evaluation period; P t type.0 represents the wind power / photovoltaic power generation / load power of the evaluation period generated by the basic model; P t type The power at time t is considered to consider the demand development; t1 M.type and (t1+1) M.type Two adjacent preset time nodes; and Indicates the wind power / photovoltaic power generation installed capacity or load demand corresponding to two adjacent preset time nodes; t M.type Indicates a specific time; Indicates the specified time node; N M.type Indicates the number of specified time nodes; represents the expected wind power / photovoltaic power generation installed capacity or load demand at the corresponding time node; C M.type It represents the set of wind power / photovoltaic power generation installed capacity or load demand at different time nodes in the future.

[0017] Furthermore, in step S3, the price-based demand response model is expressed as:

[0018]

[0019] Where, and ΔP t DR They represent the price change and load response of price-type demand response at time t respectively; and P t DR0 They represent the initial electricity price and quantity participating in price-based demand response respectively; and ΔP t DR.rate Respectively represent the proportion of change in electricity price and electricity consumption; represents the price elasticity coefficient;

[0020] For price-based demand response to participate in new energy consumption, the main influencing factor is the load's willingness to participate, which is reflected in the price-based demand response model as the change in the elasticity coefficient in the price elasticity matrix. For rigid loads, price will not be able to guide the adjustment of electricity consumption. As the flexibility and controllability of loads in the power market increase, the absolute value of the price elasticity coefficient will increase, and the guiding ability of price will be enhanced. The formula for calculating the price elasticity coefficient considering the development of load demand is as follows:

[0021]

[0022] Where, represents the set of price elasticity coefficients at different time points in the evaluation period; t M.DR Indicates a specific time. Indicates the time node specified in the evaluation cycle. N M.DR Indicates the number of specified time nodes; Indicates that at t M.DR The price elasticity coefficient at t1 M.DR and (t1+1) M.DR For two adjacent preset time nodes, and Indicates the price elasticity coefficient corresponding to two adjacent preset time nodes, Indicates the price elasticity coefficient at the preset time node t, represents the historical price elasticity coefficient, represents the price elasticity coefficient at the beginning of the evaluation period;

[0023] The incentive demand response model is expressed as:

[0024]

[0025] Where ΔP t DLC.Cin and ΔP t DLC.Cde denote the purchased incentive-based demand response negative reserve and positive reserve capacity respectively; and is the corresponding [0,1] state variable; ΔP t DLC This represents the actual daily reserve capacity. As electricity market development progresses, industrial users are more willing to participate in incentive-based demand response, and the capacity of incentive-based demand response continues to increase. Its model is a continuous-time stochastic variation model, calculated using a formula that considers price elasticity coefficients based on load demand development.

[0026] Furthermore, in step S4, the objective function of the new energy consumption capacity evaluation model is to maximize the new energy consumption rate, and the specific formula is as follows:

[0027]

[0028] Where N w 、N s are the number of wind farms and photovoltaic power stations, are the absorbed power of wind farm and photovoltaic power station respectively, and are the theoretical power of wind farm and photovoltaic power station respectively, N area is the number of partitions, is the weight coefficient of wind power and photovoltaic power consumption in region j, T is the time period for consumption capacity assessment, is the new energy consumption rate;

[0029] Constraints include power balance constraints, reserve capacity constraints, price-based demand response constraints, incentive-based demand response constraints, tie-line and transmission section constraints, renewable energy output constraints, thermal power unit constraints, cascade hydropower unit constraints, and energy storage operation constraints.

[0030] The power balance constraint calculation formula is as follows:

[0031]

[0032] Where k is the partition number, M area (k) represents the set of resources in the partition; {i G ,i w ,i s ,i H} indicates the number of the corresponding thermal power unit, wind farm, photovoltaic power station, and hydropower resource in the partition; Respectively represent the power of each thermal power unit, hydropower unit, wind farm, and photovoltaic power station at time t; Input and output power of the tie line with the external grid respectively; represents the total load power of k partition; Indicates grid loss; represents the price-based demand response adjustment quantity for k partitions; and denote the purchased incentive-based demand response negative reserve and positive reserve capacity of k zones respectively; P t ES1.in 、P t ES1.out Respectively represent the charging and discharging power of power type energy storage; P t ES2.in 、P t ES2.out Respectively represent the charging and discharging power of capacity-type energy storage;

[0033] The calculation formula for the reserve capacity constraint is as follows:

[0034]

[0035]

[0036] In the formula, RT represents spare, K w.RT , K s.RT Represent the reserve rates of wind power and photovoltaic power respectively, K ld.RT Indicates the reserve rate of load;

[0037] The price-based demand response constraint is:

[0038]

[0039] Where, They represent the minimum and maximum electricity price changes at time t, ΔP t DR.min , ΔP t DR.max They represent the minimum and maximum price-based demand response load changes at time t respectively;

[0040] The constraints of incentive-based demand response are:

[0041]

[0042] Where ΔP t DLC.Cde.max , ΔP t DLC.Cin.max Respectively represent the maximum value of positive reserve and negative reserve;

[0043] The calculation formula for tie line and transmission section constraints is as follows:

[0044]

[0045] Where, They represent the transmission capacity of the jth transmission section at time t, which is the transmission section between different sections of the target power grid and the interconnection transmission section between the target power grid and the external power grid;

[0046] The output constraints of new energy are as follows:

[0047]

[0048] Where, They represent the theoretical power of wind farm and photovoltaic power station at time t respectively; Respectively represent the absorbed power of wind farm and photovoltaic power station;

[0049] Thermal power unit constraints include power upper and lower limits, ramp power constraints, minimum start and stop time constraints, and the number of times the unit receives start and stop state commands within a cycle. The power upper and lower limits of thermal power units are:

[0050]

[0051] Where, P i G.max 、P i G.min Indicates the maximum and minimum power of thermal power units. Indicates start / stop status;

[0052] Among them, the thermal power unit climbing power constraint is:

[0053]

[0054] Where, P i G.clup.max 、P i G.cldw.max Indicates the maximum power of thermal power units climbing up and down;

[0055] Among them, the minimum start and stop time constraint of thermal power units is:

[0056]

[0057] Where, t tempt Represents any time, T on.min 、T off.min Indicates the minimum start and stop time;

[0058] Among them, the number of times the thermal power unit receives the start and stop state instructions within the cycle is constrained as follows:

[0059]

[0060] Where, T period represents the total scheduling period; Indicates the maximum number of times the start / stop state command is accepted;

[0061] The constraints of cascade hydropower units include the water balance constraints of each cascade hydropower station, the output power constraints of the hydropower station, the water storage capacity constraints of the reservoir, and the power generation flow constraints of the hydropower station. Among them, the water balance constraints of each cascade hydropower station are:

[0062] For the first-stage hydropower station:

[0063] V i.t+1 =V i.t +q 1i.t -Q 1i.t -S 1i.t

[0064] For other levels of hydropower stations:

[0065] V i.t+1 =V i.t +q i.t -Q i.t -S i.t +Q i-1.t-τ +S i-1.t-τ

[0066] Where V i.t represents the storage capacity of hydropower station i during period t, q 1i.t represents the natural water inflow of hydropower station i during period t, Q 1i.t represents the power generation flow of hydropower station i during period t, S 1i.t represents the amount of water abandoned by hydropower station i during period t, and τ represents the arrival time of water flow from the i-1th level hydropower station to the i-th level hydropower station;

[0067] The output power constraint of the hydropower station is:

[0068]

[0069] Where, represents the power of the i-th hydropower station at time t, H i.t represents the water head of the i-th hydropower station at time t, η i represents the power generation efficiency of the i-th hydropower station at time t, They represent the minimum and maximum active power of the i-th hydropower station at time t respectively;

[0070] The reservoir storage capacity constraint is:

[0071]

[0072] Where, They represent the upper and lower limits of the reservoir water storage capacity of the i-th level hydropower station at time t;

[0073] The power generation flow constraint of the hydropower station is:

[0074]

[0075] Where, Respectively represent the maximum and minimum daily flow values available for hydropower units;

[0076] The energy storage operation constraints are:

[0077]

[0078] Where, P t ES.in 、P t ES.outIndicates the energy storage charging and discharging power; P t ES.in.max 、P t ES.out.max Indicates the maximum value of energy storage charging and discharging power; Indicates the energy storage charging and discharging status; Indicates the state of charge; Indicates the minimum and maximum power; η ES.in ,η ES.out Represents the charging and discharging efficiency. The above model will serve as a constraint in the new energy absorption capacity evaluation model.

[0079] In a second aspect, the present invention provides a device for evaluating new energy consumption capacity taking into account power demand response, comprising:

[0080] A data acquisition module is used to acquire power system related data, wherein the power system related data includes wind power data, photovoltaic power generation data and load data;

[0081] Wind power, photovoltaic power generation and load power modules are used to establish wind power, photovoltaic power generation and load power models based on the acquired wind power data, photovoltaic power generation data and load data, and generate wind power, photovoltaic power generation and load power data for future periods;

[0082] The power demand response module is used to establish power demand response models, including price-based demand response models and incentive-based demand response models;

[0083] The new energy absorption capacity assessment module is used to establish a new energy absorption capacity assessment model and incorporate the established power demand response model as a control method and constraint condition into the new energy absorption capacity assessment model to form a new energy absorption capacity assessment model that takes power demand response into account;

[0084] The model solving module is used to take the power system related data and the power data of wind power, photovoltaic power generation and load in the future period as input data, and calculate the established new energy consumption capacity assessment model considering the power demand response through the optimization solution method to obtain the new energy consumption capacity assessment result considering the power demand response.

[0085] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the above-mentioned method for evaluating new energy absorption capacity taking into account power demand response.

[0086] In a fourth aspect, the present invention provides a computer-readable storage medium storing at least one instruction, which, when executed by a processor, implements the above-mentioned method for evaluating new energy absorption capacity considering power demand response.

[0087] The present invention establishes a wind power and photovoltaic power generation power model that considers the development of installed capacity, a load power model that considers the development of load demand, a price-based demand response model, an incentive-based demand response model, and a new energy absorption capacity assessment model that considers power demand response. These models can scientifically analyze the impact of power demand response on new energy absorption capacity, accurately assess new energy absorption capacity that considers power demand response, and overcome the deficiency of existing new energy absorption capacity assessment methods that do not consider power demand response as a regulatory factor. On the one hand, the present invention can quantitatively analyze the impact of power demand response on the level of new energy absorption, providing decision-making support for energy authorities to scientifically formulate policies related to power demand response; on the other hand, it can provide a basis for the rational planning and differentiated access strategies of wind power and photovoltaic power generation, and also lay the foundation for power market participants to optimize trading strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0089] Figure 1 A flow chart of a method for evaluating new energy consumption capacity considering power demand response provided by an exemplary embodiment of the present invention;

[0090] Figure 2 A schematic structural diagram of a device for evaluating new energy consumption capacity considering power demand response provided by an exemplary embodiment of the present invention;

[0091] Figure 3 A structural block diagram of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0092] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0093] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0094] Those skilled in the art will understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0095] It should also be understood that, in the embodiments of the present invention, “a plurality of” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0096] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0097] In addition, the term "and / or" in the present invention is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone.

[0098] In addition, the character “ / ” in the present invention generally indicates that the preceding and following related objects are in an “or” relationship.

[0099] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced with each other. For the sake of brevity, they will not be described one by one.

[0100] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0101] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0102] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0103] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0104] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate in conjunction with numerous other general-purpose or specialized computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with terminal devices, computer systems, servers, and other electronic devices include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above.

[0105] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media, including storage devices.

[0106] Exemplary Methods

[0107] Figure 1 This is a flow chart of a method for evaluating the new energy consumption capacity considering power demand response provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown in Figure 2, the new energy absorption capacity assessment method considering power demand response includes the following steps:

[0108] Step S1, obtaining power system related data, wherein the power system related data includes wind power data, photovoltaic power generation data and load data.

[0109] Specifically, the acquired wind power data includes historical wind power data and future installed capacity development data; the acquired photovoltaic power generation data includes historical photovoltaic power generation data and future installed capacity development data; the acquired load data includes historical load power data and future demand development data; and the acquired power system-related data also includes electricity price data, spare capacity data, transmission section data, energy storage data, conventional unit data, etc. This exemplary embodiment of the present invention conducts case analysis based on the new energy and load data of a certain region in 2022. The original power curves are all normalized. The grid structure is based on the IEEE-39 node system, and the power grid is divided into three regions.

[0110] Step S2: Based on the wind power, photovoltaic power generation and load data obtained in step S1, a power model of wind power, photovoltaic power generation and load is established to generate power data of wind power, photovoltaic power generation and load in the future period.

[0111] Specifically, the power models for wind power, photovoltaic power generation, and loads established include a basic model and a development model. The basic model first evaluates and analyzes historical power data for wind power, photovoltaic power generation, and loads at multiple time scales and dimensions, identifying the dynamic characteristics of source and load resources and determining their short-term cyclical characteristics, long-term seasonal characteristics, and capacity variation characteristics. Then, through production simulation technology, power data for wind power, photovoltaic power generation, and loads are generated for the new energy absorption capacity assessment cycle that meets the relevant characteristic indicators.

[0112] Based on the basic models of wind power, photovoltaic power generation, and load, the impact of the development of wind power and photovoltaic power generation installed capacity and load demand on their power during the assessment period is considered, and a development model of wind power, photovoltaic power generation, and load that takes into account capacity / demand development is established. The calculation formula is as follows:

[0113]

[0114] In the formula, type represents type. When type is w, it represents wind power, when type is s, it represents photovoltaic power generation, and when type is ld, it represents load. Indicates the historical installed capacity or load demand of wind power / photovoltaic power generation; The wind power / photovoltaic power generation installed capacity or load demand at time t is considered to take into account the development of wind power / photovoltaic power generation installed capacity and load demand; represents the wind power / photovoltaic power generation installed capacity or load demand at the initial moment of the evaluation period; P t type.0 represents the wind power / photovoltaic power generation / load power of the evaluation period generated by the basic model; P t type The power at time t is considered to consider the demand development; t1 M.type and (t1+1) M.type Two adjacent preset time nodes; and Indicates the wind power / photovoltaic power generation installed capacity or load demand corresponding to two adjacent preset time nodes; t M.type Indicates a specific time; Indicates the specified time node; N M.type Indicates the number of specified time nodes; represents the expected wind power / photovoltaic power generation installed capacity or load demand at the corresponding time node; C M.type It represents the set of wind power / photovoltaic power generation installed capacity or load demand at different time nodes in the future.

[0115] The exemplary embodiment of the present invention sets the wind power installed capacity development time nodes in the three sub-grids as {1; 8784}, and the corresponding installed capacities are {1; 1.35}, {1; 1.3}, and {1; 1.25}, that is, at the initial time 1, the wind power installed capacity in each sub-grid is 1; at 8784, the wind power installed capacity in each sub-grid is 1.35, 1.3, and 1.25 respectively; the photovoltaic power generation installed capacity development time nodes in the three sub-grids are {1; 1.35}, {1; 1.3}, and {1; 1.25} respectively. The nodes are {1; 3000; 7200; 8784}, and the corresponding installed capacities are {1; 1.15; 1.25; 1.3}; the load demand development time nodes in the three partitioned power grids are {1; 8784}, {1; 4000; 8784}, and {1; 4000; 8784}, and the load demand development scales in the three partitions are {1; 1.2}, {1; 1.15; 1.2}, and {1, 1.05, 1.2}.

[0116] Step S3: Establishing an electricity demand response model, including a price-based demand response model and an incentive-based demand response model.

[0117] The price-based demand response mechanism is to formulate time-of-use electricity prices. For example, the whole day is divided into three price periods: peak, flat, and valley. Under the guidance of economic benefits, electricity users spontaneously adjust their electricity consumption behavior, increasing electricity consumption during the peak period of renewable energy power generation when electricity prices are low, and reducing electricity consumption during the valley period when renewable energy power generation is high, thereby increasing the amount of renewable energy consumed. The price-based demand response model is expressed as:

[0118]

[0119] Where, and ΔP t DR They represent the price change and load response of price-type demand response at time t respectively; and P t DR0 They represent the initial electricity price and quantity participating in price-based demand response respectively; and ΔP t DR.rate Respectively represent the proportion of change in electricity price and electricity consumption; represents the price elasticity coefficient;

[0120] For price-based demand response to participate in new energy consumption, the main influencing factor is the load's willingness to participate, which is reflected in the price-based demand response model as a change in the elasticity coefficient in the price elasticity matrix. For rigid loads, price will not be able to guide the adjustment of electricity consumption. As the flexibility and controllability of loads in the electricity market increase, the absolute value of the price elasticity coefficient will increase, and the guiding ability of prices will be enhanced. The formula for calculating the price elasticity coefficient considering the development of load demand is as follows:

[0121]

[0122] Where, represents the set of price elasticity coefficients at different time points in the evaluation period; t M.DR Indicates a specific time. Indicates the time node specified in the evaluation cycle. N M.DR Indicates the number of specified time nodes; Indicates that at t M.DR The price elasticity coefficient at t1 M.DR and (t1+1) M.DR For two adjacent preset time nodes, and Indicates the price elasticity coefficient corresponding to two adjacent preset time nodes, Indicates the price elasticity coefficient at the preset time node t, represents the historical price elasticity coefficient, Represents the price elasticity coefficient at the beginning of the evaluation period.

[0123] The incentive demand response model is expressed as:

[0124]

[0125] Where ΔP t DLC.Cin and ΔP t DLC.Cde denote the purchased incentive-based demand response negative reserve and positive reserve capacity respectively; and is the corresponding [0,1] state variable; ΔP t DLC This represents the actual daily reserve capacity. As electricity market development progresses, industrial users are more willing to participate in incentive-based demand response, and the capacity of incentive-based demand response continues to increase. Its model is a continuous-time stochastic variation model, calculated using a formula that considers price elasticity coefficients based on load demand development.

[0126] In an exemplary embodiment of the present invention, the time nodes of price-type demand response in three partitioned power grids are set to {1; 8784}, {1; 4000; 8784}, and {1; 4000; 8784}, and the changes in the load elasticity coefficients of price-type demand response in the three partitioned power grids are {1; 1.2}, {1; 1.15; 1.2}, and {1, 1.05, 1.2}; the time node of incentive-type demand response is {1; 8784}, and the change in the load participation ratio of incentive-type demand response is {1; 1.2}.

[0127] Step S4: Establish a new energy absorption capacity assessment model with the maximum new energy absorption rate as the objective function, and add the power demand response model established in step S3 as a control means and constraint condition to the new energy absorption capacity assessment model to form a new energy absorption capacity assessment model that takes power demand response into consideration.

[0128] Specifically, the new energy consumption capacity assessment model includes an objective function and constraints, where the objective function is to maximize the new energy consumption rate. The specific formula is as follows:

[0129]

[0130] Where N w 、N s are the number of wind farms and photovoltaic power stations, are the absorbed power of wind farm and photovoltaic power station respectively, and are the theoretical power of wind farm and photovoltaic power station respectively, N area is the number of partitions, is the weight coefficient of wind power and photovoltaic power consumption in region j, T is the time period for consumption capacity assessment, is the new energy consumption rate;

[0131] The constraints include power balance constraints, reserve capacity constraints, price-based demand response constraints, incentive-based demand response constraints, interconnection line and transmission section constraints, new energy output constraints, thermal power unit constraints, cascade hydropower unit constraints, and energy storage operation constraints.

[0132] The power balance constraint calculation formula is as follows:

[0133]

[0134] Where k is the partition number, M area (k) represents the set of resources in the partition; {i G ,i w ,i s ,i H} indicates the number of the corresponding thermal power unit, wind farm, photovoltaic power station, and hydropower resource in the partition; Respectively represent the power of each thermal power unit, hydropower unit, wind farm, and photovoltaic power station at time t; Input and output power of the tie line with the external grid respectively; represents the total load power of k partition; Indicates grid loss; represents the price-based demand response adjustment quantity for k partitions; and denote the purchased incentive-based demand response negative reserve and positive reserve capacity of k zones respectively; P t ES1.in 、P t ES1.out Respectively represent the charging and discharging power of power type energy storage; P t ES2.in 、P t ES2.out Respectively represent the charging and discharging power of capacity-type energy storage;

[0135] The calculation formula for the reserve capacity constraint is as follows:

[0136]

[0137] In the formula, RT represents spare, K w.RT , K s.RT Represent the reserve rates of wind power and photovoltaic power respectively, K ld.RT Indicates the reserve rate of load;

[0138] The price-based demand response constraint is:

[0139]

[0140] Where, They represent the minimum and maximum electricity price changes at time t, ΔP t DR.min , ΔP t DR.max They represent the minimum and maximum price-based demand response load changes at time t respectively;

[0141] The constraints of incentive-based demand response are:

[0142]

[0143] Where ΔP t DLC.Cde.max , ΔP t DLC.Cin.max Respectively represent the maximum value of positive reserve and negative reserve;

[0144] The calculation formula for tie line and transmission section constraints is as follows:

[0145]

[0146] Where, They represent the transmission capacity of the jth transmission section at time t, which is the transmission section between different sections of the target power grid and the interconnection transmission section between the target power grid and the external power grid;

[0147] The output constraints of new energy are as follows:

[0148]

[0149] Where, They represent the theoretical power of wind farm and photovoltaic power station at time t respectively; Respectively represent the absorbed power of wind farm and photovoltaic power station;

[0150] Thermal power unit constraints include power upper and lower limits, ramp power constraints, minimum start and stop time constraints, and the number of times the unit receives start and stop state commands within a cycle. The power upper and lower limits of thermal power units are:

[0151]

[0152] Where, P i G.max 、P i G.min Indicates the maximum and minimum power of thermal power units. Indicates start / stop status;

[0153] Among them, the thermal power unit climbing power constraint is:

[0154]

[0155] Where, P i G.clup.max 、P i G.cldw.max Indicates the maximum power of thermal power units climbing up and down;

[0156] Among them, the minimum start and stop time constraint of thermal power units is:

[0157]

[0158] Where, t tempt Represents any time, T on.min 、T off.min Indicates the minimum start and stop time;

[0159] Among them, the number of times the thermal power unit receives the start and stop state instructions within the cycle is constrained as follows:

[0160]

[0161] Where, T period represents the total scheduling period; Indicates the maximum number of times the start / stop state command is accepted;

[0162] The constraints of cascade hydropower units include the water balance constraints of each cascade hydropower station, the output power constraints of the hydropower station, the water storage capacity constraints of the reservoir, and the power generation flow constraints of the hydropower station. Among them, the water balance constraints of each cascade hydropower station are:

[0163] For the first-stage hydropower station:

[0164] V i.t+1 =V i.t +q 1i.t -Q 1i.t -S 1i.t

[0165] For other levels of hydropower stations:

[0166] V i.t+1 =V i.t +q i.t -Q i.t -S i.t +Q i-1.t-τ +S i-1.t-τ

[0167] Where V i.t represents the storage capacity of hydropower station i during period t, q 1i.t represents the natural water inflow of hydropower station i during period t, Q 1i.t represents the power generation flow of hydropower station i during period t, S 1i.t represents the amount of water abandoned by hydropower station i during period t, and τ represents the arrival time of water flow from the i-1th level hydropower station to the i-th level hydropower station;

[0168] Among them, the output power constraint of the hydropower station is:

[0169]

[0170] Where, represents the power of the i-th hydropower station at time t, H i.t represents the water head of the i-th hydropower station at time t, η i represents the power generation efficiency of the i-th hydropower station at time t, They represent the minimum and maximum active power of the i-th hydropower station at time t respectively;

[0171] The reservoir storage capacity constraint is:

[0172]

[0173] Where, They represent the upper and lower limits of the reservoir water storage capacity of the i-th level hydropower station at time t;

[0174] The power generation flow constraint of the hydropower station is:

[0175]

[0176] Where, Respectively represent the maximum and minimum daily flow values available for hydropower units;

[0177] The energy storage operation constraints are:

[0178]

[0179] Where, P t ES.in 、P t ES.out Indicates the energy storage charging and discharging power; P t ES.in.max 、P t ES.out.max Indicates the maximum value of energy storage charging and discharging power; Indicates the energy storage charging and discharging status; Indicates the state of charge; Indicates the minimum and maximum power; η ES.in ,η ES.out Represents the charging and discharging efficiency. The above model will serve as a constraint in the new energy absorption capacity evaluation model.

[0180] Step S5: Using the power system related data obtained in step S1 and the power data of wind power, photovoltaic power generation and load in the future period obtained in step S2 as input data, the new energy absorption capacity assessment model considering power demand response established in step S4 is calculated through the optimization solution method to obtain the new energy absorption capacity assessment result considering power demand response.

[0181] The evaluation results of the new energy absorption capacity of the three partitioned power grids in the basic scenario of the exemplary embodiment of the present invention are shown in Table 1; the evaluation results of the new energy absorption capacity taking into account the power demand response are shown in Table 2.

[0182] Table 1 Comparison of new energy consumption rates in various regions under basic scenarios

[0183]

[0184] Table 2 Comparison of regional new energy consumption rates considering power demand response

[0185]

[0186]

[0187] Exemplary devices

[0188] Figure 2 This is a schematic diagram of a new energy consumption capacity evaluation device considering power demand response provided by an exemplary embodiment of the present invention. Figure 2 As shown, the apparatus 200 includes:

[0189] A data acquisition module 201 is used to acquire power system related data, including wind power data, photovoltaic power generation data, and load data;

[0190] Wind power, photovoltaic power generation and load power module 202, used to establish wind power, photovoltaic power generation and load power models based on the acquired wind power data, photovoltaic power generation data and load data, and generate wind power, photovoltaic power generation and load power data for future time periods;

[0191] The power demand response module 203 is used to establish a power demand response model, including a price-based demand response model and an incentive-based demand response model;

[0192] The new energy absorption capacity assessment module 204 is used to establish a new energy absorption capacity assessment model and add the established power demand response model as a control method and constraint condition to the new energy absorption capacity assessment model to form a new energy absorption capacity assessment model that takes power demand response into account;

[0193] The model solving module 205 is used to take the power system related data and the power data of wind power, photovoltaic power generation and load in the future period as input data, and calculate the established new energy absorption capacity evaluation model considering the power demand response through the optimization solution method to obtain the new energy absorption capacity evaluation result considering the power demand response.

[0194] Optionally, the data acquisition module 201 acquires power system-related data including historical power data of wind power and photovoltaic power generation and future installed capacity development data, historical power data of loads and future demand development data, electricity price data, spare capacity data, transmission section data, energy storage data, conventional unit data, etc.

[0195] Optionally, the wind power, photovoltaic power generation, and load power module 202 establishes wind power, photovoltaic power generation, and load power models, including a basic model and a development model. The basic model first evaluates and analyzes historical power data of wind power, photovoltaic power generation, and load at multiple time scales and dimensions, identifies the dynamic characteristics of source and load resources, and determines their short-term cyclical characteristics, long-term seasonal characteristics, and capacity change characteristics. It then uses production simulation technology to obtain wind power, photovoltaic power generation, and load power data for the new energy absorption capacity assessment period that meets relevant characteristic indicators.

[0196] Based on the basic models of wind power, photovoltaic power generation, and load, the impact of the development of wind power and photovoltaic power generation installed capacity and load demand on their power during the assessment period is considered, and a development model of wind power, photovoltaic power generation, and load that takes into account capacity / demand development is established. The calculation formula is as follows:

[0197]

[0198] In the formula, type represents type. When type is w, it represents wind power, when type is s, it represents photovoltaic power generation, and when type is ld, it represents load. Indicates the historical installed capacity or load demand of wind power / photovoltaic power generation; The wind power / photovoltaic power generation installed capacity or load demand at time t is considered to take into account the development of wind power / photovoltaic power generation installed capacity and load demand; represents the wind power / photovoltaic power generation installed capacity or load demand at the initial moment of the evaluation period; P t type.0 represents the wind power / photovoltaic power generation / load power of the evaluation period generated by the basic model; P t type The power at time t is considered to consider the demand development; t1 M.type and (t1+1) M.type Two adjacent preset time nodes; and Indicates the wind power / photovoltaic power generation installed capacity or load demand corresponding to two adjacent preset time nodes; t M.type Indicates a specific time; Indicates the specified time node; N M.type Indicates the number of specified time nodes; represents the expected wind power / photovoltaic power generation installed capacity or load demand at the corresponding time node; C M.type It represents the set of wind power / photovoltaic power generation installed capacity or load demand at different time nodes in the future.

[0199] Optionally, the power demand response module 203 establishes a power demand response model, including a price-based demand response model and an incentive-based demand response model. The price-based demand response model is expressed as:

[0200]

[0201] Where, and ΔP t DR They represent the price change and load response of price-type demand response at time t respectively; and P t DR0 They represent the initial electricity price and quantity participating in price-based demand response respectively; and ΔP t DR.rate Respectively represent the proportion of change in electricity price and electricity consumption; Represents the price elasticity coefficient.

[0202] The formula for calculating the price elasticity coefficient considering the development of load demand is as follows:

[0203]

[0204] Where, represents the set of price elasticity coefficients at different time points in the evaluation period; t M.DR Indicates a specific time. Indicates the time node specified in the evaluation cycle. N M.DR Indicates the number of specified time nodes; Indicates that at t M.DR The price elasticity coefficient at t1 M.DR and (t1+1) M.DR For two adjacent preset time nodes, and Indicates the price elasticity coefficient corresponding to two adjacent preset time nodes, Indicates the price elasticity coefficient at the preset time node t, represents the historical price elasticity coefficient, Represents the price elasticity coefficient at the beginning of the evaluation period.

[0205] The incentive demand response model is expressed as:

[0206]

[0207] Where ΔP t DLC.Cin and ΔP t DLC.Cde denote the purchased incentive-based demand response negative reserve and positive reserve capacity respectively; and is the corresponding [0,1] state variable; ΔP t DLC This represents the actual daily reserve capacity. As electricity market development progresses, industrial users are more willing to participate in incentive-based demand response, and the capacity of incentive-based demand response continues to increase. Its model is a continuous-time stochastic variation model, calculated using a formula that considers price elasticity coefficients based on load demand development.

[0208] Optionally, the new energy consumption capacity evaluation module 204 includes a new energy consumption capacity evaluation model including an objective function and constraints, wherein the objective function is to maximize the new energy consumption rate, and the specific formula is as follows:

[0209]

[0210] Where N w 、N s are the number of wind farms and photovoltaic power stations, are the absorbed power of wind farm and photovoltaic power station respectively, and are the theoretical power of wind farm and photovoltaic power station respectively, N area is the number of partitions, is the weight coefficient of wind power and photovoltaic power consumption in region j, T is the time period for consumption capacity assessment, is the new energy consumption rate.

[0211] The constraints include power balance constraints, reserve capacity constraints, price-based demand response constraints, incentive-based demand response constraints, interconnection line and transmission section constraints, new energy output constraints, thermal power unit constraints, cascade hydropower unit constraints, and energy storage operation constraints.

[0212] The power balance constraint calculation formula is as follows:

[0213]

[0214] Where k is the partition number, M area (k) represents the set of resources in the partition; {i G ,i w ,i s ,i H} indicates the number of the corresponding thermal power unit, wind farm, photovoltaic power station, and hydropower resource in the partition; Respectively represent the power of each thermal power unit, hydropower unit, wind farm, and photovoltaic power station at time t; Input and output power of the tie line with the external grid respectively; represents the total load power of k partition; Indicates grid loss; represents the price-based demand response adjustment quantity for k partitions; and denote the purchased incentive-based demand response negative reserve and positive reserve capacity of k zones respectively; P t ES1.in 、P t ES1.out Respectively represent the charging and discharging power of power type energy storage; P t ES2.in 、P t ES2.out Respectively represent the charging and discharging power of capacity-type energy storage.

[0215] The calculation formula for the reserve capacity constraint is as follows:

[0216]

[0217] In the formula, RT represents spare, K w.RT , K s.RT Represent the reserve rates of wind power and photovoltaic power respectively, Kld.RT Indicates the load reserve ratio.

[0218] The price-based demand response constraint is:

[0219]

[0220] Where, They represent the minimum and maximum electricity price changes at time t, ΔP t DR.min , ΔP t DR.max They represent the minimum and maximum price-based demand response load changes at time t respectively.

[0221] The constraints of incentive-based demand response are:

[0222]

[0223] Where ΔP t DLC.Cde.max , ΔP t DLC.Cin.max Respectively represent the maximum values of positive reserve and negative reserve.

[0224] The calculation formula for tie line and transmission section constraints is as follows:

[0225]

[0226] Where, They represent the transmission capacity of the jth transmission section at time t, which is the transmission section between different sections of the target power grid and the interconnection transmission section between the target power grid and the external power grid;

[0227] The output constraints of new energy are as follows:

[0228]

[0229] Where, They represent the theoretical power of wind farm and photovoltaic power station at time t respectively; They represent the absorbed power of wind farms and photovoltaic power stations respectively.

[0230] Thermal power unit constraints include power upper and lower limits, ramp power constraints, minimum start and stop time constraints, and the number of times the unit receives start and stop state commands within a cycle. The power upper and lower limits of thermal power units are:

[0231]

[0232] Where, P i G.max 、P i G.min Indicates the maximum and minimum power of thermal power units. Indicates the start / stop status.

[0233] Among them, the thermal power unit climbing power constraint is:

[0234]

[0235] Where, P i G.clup.max 、P i G.cldw.max Indicates the maximum power of the thermal power unit when climbing up and down.

[0236] Among them, the minimum start and stop time constraint of thermal power units is:

[0237]

[0238] Where, t tempt Represents any time, T on.min 、T off.min Indicates the minimum start and stop time.

[0239] Among them, the number of times the thermal power unit receives the start and stop state instructions within the cycle is constrained as follows:

[0240]

[0241] Where, T period represents the total scheduling period; Indicates the maximum number of times the start / stop state command is accepted.

[0242] The constraints of cascade hydropower units include the water balance constraints of each cascade hydropower station, the output power constraints of the hydropower station, the water storage capacity constraints of the reservoir, and the power generation flow constraints of the hydropower station. Among them, the water balance constraints of each cascade hydropower station are:

[0243] For the first-stage hydropower station:

[0244] V i.t+1 =V i.t +q 1i.t -Q 1i.t -S 1i.t

[0245] For other levels of hydropower stations:

[0246] V i.t+1 =V i.t +q i.t -Q i.t -S i.t +Q i-1.t-τ +S i-1.t-τ

[0247] Where V i.t represents the storage capacity of hydropower station i during period t, q1i.t represents the natural water inflow of hydropower station i during period t, Q 1i.t represents the power generation flow of hydropower station i during period t, S 1i.t represents the amount of water abandoned by hydropower station i during period t, and τ represents the arrival time of water flow from the i-1th hydropower station to the i-th hydropower station.

[0248] Among them, the output power constraint of the hydropower station is:

[0249]

[0250] Where, represents the power of the i-th hydropower station at time t, H i.t represents the water head of the i-th hydropower station at time t, η i represents the power generation efficiency of the i-th hydropower station at time t, They represent the minimum and maximum active power of the i-th hydropower station at time t respectively.

[0251] The reservoir storage capacity constraint is:

[0252]

[0253] Where, They represent the upper and lower limits of the reservoir water storage capacity of the i-th level hydropower station at time t.

[0254] The power generation flow constraint of the hydropower station is:

[0255]

[0256] Where, They respectively represent the maximum and minimum daily flow values available for the hydropower units.

[0257] The energy storage operation constraints are:

[0258]

[0259] Where, P t ES.in 、P t ES.out Indicates the energy storage charging and discharging power; P t ES.in.max 、P t ES.out.max Indicates the maximum value of energy storage charging and discharging power; Indicates the energy storage charging and discharging status; Indicates the state of charge; Indicates the minimum and maximum power; η ES.in ,η ES.out Represents the charging and discharging efficiency. The above model will serve as a constraint in the new energy absorption capacity evaluation model.

[0260] Optionally, the model solving module 205 uses the power system related data obtained by the data acquisition module 201 and the wind power, photovoltaic power generation power, load power and other data obtained by the wind power, photovoltaic power generation and load power module 202 as input data, and uses an optimization solution method to calculate the new energy absorption capacity evaluation model considering the power demand response established by the new energy absorption capacity evaluation module 204, thereby obtaining the new energy absorption capacity evaluation result considering the power demand response.

[0261] Exemplary electronic devices

[0262] Figure 3 FIG1 is a block diagram of an electronic device provided by an exemplary embodiment of the present invention. Figure 3 As shown, the electronic device 300 includes one or more processors 301 and a memory 302 .

[0263] The processor 301 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0264] The memory 302 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM), cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 301 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may further include: an input device 303 and an output device 304, and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0265] In addition, the input device 303 may also include a keyboard, a mouse, etc.

[0266] The output device 304 can output various information to the outside, and can include a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0267] Of course, to simplify, Figure 3Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0268] Exemplary computer program products and computer-readable storage media

[0269] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to perform the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0270] The computer program product may be written in any combination of one or more programming languages to implement the operations of embodiments of the present invention, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as C or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0271] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0272] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0273] The basic principles of the present invention have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in the present invention are merely illustrative and non-limiting, and should not be construed as necessarily possessed by each embodiment of the present invention. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, and are not intended to be limiting. These details do not necessarily limit the present invention to being implemented using these specific details.

[0274] Each embodiment in this specification is described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. Reference can be made to the descriptions of the identical or similar parts between the various embodiments. For the device embodiments, since they are essentially identical to the method embodiments, their descriptions are relatively simple. For relevant parts, reference can be made to the descriptions of the method embodiments.

[0275] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0276] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above, unless otherwise specified. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers recording media that store programs for executing the method according to the present invention.

[0277] It should also be noted that, in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in this field to make or use the present invention. Various modifications to these aspects will be very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but according to the widest scope consistent with the principles disclosed here and novel features.

[0278] The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. While various exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize that certain variations, modifications, alterations, additions, and sub-combinations thereof are intended to fall within the scope of the claims of the present invention.

Claims

1. A new energy consumption capacity assessment method considering power demand response is characterized by: include: Step S1: Acquire power system related data, wherein the power system related data includes wind power data, photovoltaic power generation data and load data; Step S2: Based on the wind power data, photovoltaic power generation data and load data obtained in step S1, a power model of wind power, photovoltaic power generation and load is established to generate power data of wind power, photovoltaic power generation and load in the future period; Step S3: Establishing an electricity demand response model, including a price-based demand response model and an incentive-based demand response model; Step S4: Establish a new energy consumption capacity assessment model, and add the power demand response model established in step S3 as a control method and constraint condition to the new energy consumption capacity assessment model to form a new energy consumption capacity assessment model that takes power demand response into account; Step S5: Using the power system related data obtained in step S1 and the power data of wind power, photovoltaic power generation and load in the future period obtained in step S2 as input data, the new energy absorption capacity assessment model considering power demand response established in step S4 is calculated through the optimization solution method to obtain the new energy absorption capacity assessment result considering power demand response.

2. The method according to claim 1, characterized in that In step S1, the wind power data includes historical power data and future installed capacity development data of wind power, the photovoltaic power generation data includes historical power data and future installed capacity development data of photovoltaic power generation, the load data includes historical power data and future demand development data of load, and the power system related data also includes electricity price data, spare capacity data, transmission section data, energy storage data, conventional unit data, etc.

3. The method according to claim 1, characterized in that In step S2, the power models of wind power, photovoltaic power generation, and load established include a basic model and a development model. The basic model first identifies the dynamic characteristics of source and load resources by evaluating and analyzing historical power data of wind power, photovoltaic power generation, and load at multiple time scales and dimensions, and determines the short-term periodic characteristics, long-term seasonal characteristics, and capacity change characteristics of the source and load resources. Then, through production simulation technology, the power data of wind power, photovoltaic power generation and load in the new energy absorption capacity assessment cycle that meets the relevant characteristic indicators are obtained; Based on the basic models of wind power, photovoltaic power generation, and load, the impact of the development of wind power and photovoltaic power generation installed capacity and load demand on their power during the assessment period is considered, and a development model of wind power, photovoltaic power generation, and load that takes into account capacity / demand development is established. The calculation formula is as follows: In the formula, type represents type. When type is w, it represents wind power, when type is s, it represents photovoltaic power generation, and when type is ld, it represents load. Indicates the historical installed capacity or load demand of wind power / photovoltaic power generation; The wind power / photovoltaic power generation installed capacity or load demand at time t is considered to take into account the development of wind power / photovoltaic power generation installed capacity and load demand; represents the wind power / photovoltaic power generation installed capacity or load demand at the initial moment of the evaluation period; P t type.0 represents the wind power / photovoltaic power generation / load power of the evaluation period generated by the basic model; P t type The power at time t is considered to consider the demand development; t1 M.type and (t1+1) M.type Two adjacent preset time nodes; and Indicates the wind power / photovoltaic power generation installed capacity or load demand corresponding to two adjacent preset time nodes; t M.type Indicates a specific time; Indicates the specified time node; N M.type Indicates the number of specified time nodes; represents the expected wind power / photovoltaic power generation installed capacity or load demand at the corresponding time node; C M.type It represents the set of wind power / photovoltaic power generation installed capacity or load demand at different time nodes in the future.

4. The method according to claim 1, wherein In step S3, the price-based demand response model is expressed as: Where, and ΔP t DR They represent the price change and load response of price-type demand response at time t respectively; and P t DR0 They represent the initial electricity price and quantity participating in price-based demand response respectively; and ΔP t DR.rate Respectively represent the proportion of change in electricity price and electricity consumption; represents the price elasticity coefficient; For price-based demand response to participate in new energy consumption, the main influencing factor is the load's willingness to participate, which is reflected in the price-based demand response model as the change in the elasticity coefficient in the price elasticity matrix. For rigid loads, price will not be able to guide the adjustment of electricity consumption. As the flexibility and controllability of loads in the power market increase, the absolute value of the price elasticity coefficient will increase, and the guiding ability of price will be enhanced. The formula for calculating the price elasticity coefficient considering the development of load demand is as follows: Where, represents the set of price elasticity coefficients at different time points in the evaluation period; t M.DR Indicates a specific time. Indicates the time node specified in the evaluation cycle. N M.DR Indicates the number of specified time nodes; Indicates that at t M.DR The price elasticity coefficient at t1 M.DR and (t1+1) M.DR For two adjacent preset time nodes, and Indicates the price elasticity coefficient corresponding to two adjacent preset time nodes, Indicates the price elasticity coefficient at the preset time node t, represents the historical price elasticity coefficient, represents the price elasticity coefficient at the beginning of the evaluation period; The incentive demand response model is expressed as: Where ΔP t DLC.Cin and ΔP t DLC.Cde denote the purchased incentive-based demand response negative reserve and positive reserve capacity respectively; and is the corresponding [0,1] state variable; ΔP t DLC This is the spare capacity actually called upon during the day.

5. The method according to claim 1, characterized in that In step S4, the objective function of the new energy consumption capacity evaluation model is to maximize the new energy consumption rate. The specific formula is as follows: Where N w 、N s are the number of wind farms and photovoltaic power stations, are the absorbed power of wind farm and photovoltaic power station respectively, and are the theoretical power of wind farm and photovoltaic power station respectively, N area is the number of partitions, is the weight coefficient of wind power and photovoltaic power consumption in region j, T is the time period for consumption capacity assessment, is the new energy consumption rate; Constraints include power balance constraints, reserve capacity constraints, price-based demand response constraints, incentive-based demand response constraints, tie-line and transmission section constraints, renewable energy output constraints, thermal power unit constraints, cascade hydropower unit constraints, and energy storage operation constraints. The power balance constraint calculation formula is as follows: Where k is the partition number, M area (k) represents the set of resources in the partition; {i G ,i w ,i s ,i H } indicates the number of the corresponding thermal power unit, wind farm, photovoltaic power station, and hydropower resource in the partition; Respectively represent the power of each thermal power unit, hydropower unit, wind farm, and photovoltaic power station at time t; Input and output power of the tie line with the external grid respectively; represents the total load power of k partition; Indicates grid loss; represents the price-based demand response adjustment quantity for k partitions; and denote the purchased incentive-based demand response negative reserve and positive reserve capacity of k zones respectively; P t ES1.in 、P t ES1.out Respectively represent the charging and discharging power of power type energy storage; P t ES2.in 、P t ES2.out Respectively represent the charging and discharging power of capacity-type energy storage; The calculation formula for the reserve capacity constraint is as follows: In the formula, RT represents spare, K w.RT , K s.RT Represent the reserve rates of wind power and photovoltaic power respectively, K ld.RT Indicates the reserve rate of load; The price-based demand response constraint is: Where, They represent the minimum and maximum electricity price changes at time t, ΔP t DR.min , ΔP t DR.max They represent the minimum and maximum price-based demand response load changes at time t respectively; The constraints of incentive-based demand response are: Where ΔP t DLC.Cde.max , ΔP t DLC.Cin.max Respectively represent the maximum value of positive reserve and negative reserve; The calculation formula for tie line and transmission section constraints is as follows: Where, They represent the transmission capacity of the jth transmission section at time t, which is the transmission section between different sections of the target power grid and the interconnection transmission section between the target power grid and the external power grid; The output constraints of new energy are as follows: Where, They represent the theoretical power of wind farm and photovoltaic power station at time t respectively; Respectively represent the absorbed power of wind farm and photovoltaic power station; Thermal power unit constraints include upper and lower power limits, ramp power constraints, minimum start and stop time constraints, and the number of times the unit receives start and stop status commands within a cycle. The upper and lower power limits of thermal power units are: Where, P i G.max 、P i G.min Indicates the maximum and minimum power of thermal power units. Indicates start / stop status; Among them, the thermal power unit climbing power constraint is: Where, P i G.clup.max 、P i G.cldw.max Indicates the maximum power of thermal power units climbing up and down; Among them, the minimum start and stop time constraint of thermal power units is: Where, t tempt Represents any time, T on.min 、T off.min Indicates the minimum start and stop time; Among them, the number of times the thermal power unit receives the start and stop state instructions within the cycle is constrained as follows: Where, T period represents the total scheduling period; Indicates the maximum number of times the start / stop state command is accepted; The constraints of cascade hydropower units include the water balance constraints of each cascade hydropower station, the output power constraints of the hydropower station, the water storage capacity constraints of the reservoir, and the power generation flow constraints of the hydropower station. Among them, the water balance constraints of each cascade hydropower station are: For the first-stage hydropower station: V i.t+1 =V i.t +q 1i.t -Q 1i.t -S 1i.t For other levels of hydropower stations: V i.t+1 =V i.t +q i.t -Q i.t -S i.t +Q i-1.t-τ +S i-1.t-τ Where V i.t represents the storage capacity of hydropower station i during period t, q 1i.t represents the natural water inflow of hydropower station i during period t, Q 1i.t represents the power generation flow of hydropower station i during period t, S 1i.t represents the amount of water abandoned by hydropower station i during period t, and τ represents the arrival time of water flow from the i-1th level hydropower station to the i-th level hydropower station; The output power constraint of the hydropower station is: Where, represents the power of the i-th hydropower station at time t, H i.t represents the water head of the i-th hydropower station at time t, η i represents the power generation efficiency of the i-th hydropower station at time t, They represent the minimum and maximum active power of the i-th hydropower station at time t respectively; The reservoir storage capacity constraint is: Where, They represent the upper and lower limits of the reservoir water storage capacity of the i-th level hydropower station at time t; The power generation flow constraint of the hydropower station is: Where, Respectively represent the maximum and minimum daily flow values available for hydropower units; The energy storage operation constraints are: Where, P t ES.in 、P t ES.out Indicates the energy storage charging and discharging power; P t ES.in.max 、P t ES.out.max Indicates the maximum value of energy storage charging and discharging power; Indicates the energy storage charging and discharging status; Indicates the state of charge; Indicates the minimum and maximum power; η ES.in ,η ES.out Represents the charging and discharging efficiency. The above model will serve as a constraint in the new energy absorption capacity evaluation model.

6. A device for evaluating the capacity of new energy consumption considering power demand response, characterized in that: include: A data acquisition module is used to acquire power system related data, wherein the power system related data includes wind power data, photovoltaic power generation data and load data; Wind power, photovoltaic power generation and load power modules are used to establish wind power, photovoltaic power generation and load power models based on the acquired wind power data, photovoltaic power generation data and load data, and generate wind power, photovoltaic power generation and load power data for future periods; The power demand response module is used to establish power demand response models, including price-based demand response models and incentive-based demand response models; The new energy absorption capacity assessment module is used to establish a new energy absorption capacity assessment model and incorporate the established power demand response model as a control method and constraint condition into the new energy absorption capacity assessment model to form a new energy absorption capacity assessment model that takes power demand response into account; The model solving module is used to take the power system related data and the power data of wind power, photovoltaic power generation and load in the future period as input data, and calculate the established new energy consumption capacity assessment model considering the power demand response through the optimization solution method to obtain the new energy consumption capacity assessment result considering the power demand response.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the method for evaluating the new energy absorption capacity considering the power demand response as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the method for evaluating the new energy absorption capacity considering the power demand response according to any one of claims 1 to 5 is implemented.

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