Power grid dispatching method in energy storage participation scene

Abstract

The invention discloses a power grid dispatching method in an energy storage participation scene. The method comprises the following steps: establishing a master-slave game system taking an energy storage end of a demand side of a power distribution network as an upper layer and an electrical load end of the demand side as a lower layer, wherein the master-slave game system comprises an upper-layer energy storage model and a lower-layer electrical load model; inputting the scheduling capacity and the scheduling ratio of the energy storage end into the upper-layer model, outputting electric quantity transmission cost parameters of the energy storage end and the electric load end, inputting the electric quantity transmission cost parameters into the lower-layer model, outputting the transmission electric quantity of the energy storage end and the electric load end after processing, and inputting the transmission electric quantity into the upper-layer model for circulation until a variable reaches a steady-state value, and obtaining the scheduling amount to realize the scheduling of the power grid. According to the method, dynamic collaborative optimization of energy storage and power utilization load side resources can be realized, the problems of low resource utilization rate and insufficient model precision in the prior art are solved, the overall optimization and scheduling flexibility of an energy system is remarkably improved, and the technical blank in the field of collaborative optimization and dynamic interaction in the prior art is filled.

Description

Technical Field

[0001] This invention relates to a grid dispatching method in a scenario involving energy storage, and specifically to a grid dispatching method in a scenario involving energy storage. Background Technology

[0002] As a core component of distributed energy systems, energy storage technology development has primarily revolved around single-level optimization. Existing technologies generally employ single-layer or static two-layer optimization models. For example, most research focuses on energy storage and grid interaction strategies, reducing user electricity costs through peak-valley arbitrage or demand response, but fails to deeply integrate dynamic cost parameter mechanisms for ancillary services. Furthermore, energy storage degradation costs are often simplified to fixed loss coefficients, ignoring the dynamic impact of charge-discharge depth and cycle count on battery life, leading to assessment biases. Simultaneously, scheduling models for load-side resources (such as electric vehicles and air conditioners) often employ independent optimization, lacking coordination mechanisms with energy storage systems and failing to fully exploit the adjustment potential of flexible resources.

[0003] Current research has constructed a master-slave game framework with integrated energy supply plants as leaders and new energy combined cooling, heating, and power plants and load aggregators as followers. However, it fails to consider the dynamic constraints of flexible resources on the load side (such as air conditioning thermodynamic models and electric vehicle charging efficiency) and does not integrate ancillary services, resulting in limited applicability of the model to multiple collaborations. Other studies have designed two-layer optimization models incorporating electricity / heat demand response, but lack a dynamic interaction mechanism in the master-slave game. The interaction parameters between energy storage and electricity load are statically transferred, leading to optimization results that deviate from actual dynamic demand. Furthermore, ancillary services are not covered, and the operational constraints of load-side equipment (such as air conditioning thermodynamic models and electric vehicle charge state equations) are simplified, resulting in insufficient scheduling accuracy. Still other studies have proposed a two-way master-slave game model integrating electrical energy and peak-shaving ancillary services, but it does not involve a point-to-point mechanism on the load side and does not dynamically correlate the real-time scheduling ratio of ancillary service power. Other studies have designed a master-slave game model between microgrids and electric vehicles, but failed to consider the impact of bounded rationality on strategy selection on the load side (such as non-optimal responses under information asymmetry), and did not integrate the dynamic lifetime model of the energy storage system with multiple scenarios. Furthermore, the simplification of the air conditioning thermodynamic model (such as ignoring thermal inertia effects) limits the accuracy of load regulation. Other studies have verified the collaborative optimization effect of energy storage based on multi-agent stochastic games and reinforcement learning frameworks, but failed to address the lack of equilibrium characteristics in multi-player games (such as the existence and commutativity of Nash equilibrium), and the models are sensitive to parameters, requiring high-precision historical data support. In addition, the lack of a hierarchical master-slave game structure fails to reflect the differences in decision-making order in actual energy transmission. Summary of the Invention

[0004] To address the problems existing in the background technology, the present invention provides a grid dispatching method in a scenario involving energy storage.

[0005] The technical solution adopted in this invention is:

[0006] The grid dispatching method for energy storage participation scenarios of the present invention includes:

[0007] Step 1) Establish a master-slave game system with the energy storage end on the demand side of the distribution network as the upper layer and the electricity load end on the demand side as the lower layer. The master-slave game system includes an upper-layer energy storage model and a lower-layer electricity load model.

[0008] Step 2) Input the dispatch capacity of the energy storage terminal participating in the grid's ancillary services and the actual dispatch ratio into the upper-level energy storage model. After processing, output the power transmission cost parameters of the energy storage terminal and the power load terminal, and then input them into the lower-level power load model. After processing, output the transmitted power of the energy storage terminal and the power load terminal, and then input them into the upper-level energy storage model continuously. The cost can be specifically measured in terms of power. Until the variables in the master-slave game system reach a steady state value, the upper-level energy storage model outputs the transmitted power of the energy storage terminal and the grid as the dispatch quantity, and the lower-level power load model outputs the power consumption of the power load terminal and the power input from the grid as the dispatch quantity, so as to realize the dispatch of the grid.

[0009] In step 1), the upper-layer energy storage model is as follows:

[0010] maxF1+F2-F3

[0011]

[0012] Where F1 and F2 are the input costs of energy storage participating in the power grid and participating in ancillary services, respectively; F3 is the degradation cost of energy storage; and T is the optimization period. and P represents the energy cost parameters of the energy storage terminal outputting electricity to the grid and the energy cost parameters of the energy storage terminal inputting electricity from the grid at time t, respectively. t B2G and P t G2B These represent the output power from the energy storage terminal to the grid and the input power from the grid to the energy storage terminal at time t, respectively; N is the number of electrical load terminals within the grid. and These are the output power cost parameters from the energy storage terminal to the power load terminal at time t and the input power cost parameters from the power load terminal to the energy storage terminal, respectively. and These represent the output power from the energy storage terminal to the electrical load terminal i at time t and the input power from the electrical load terminal to the energy storage terminal, respectively. P represents the day-ahead cost parameter for energy storage participating in ancillary services of the power grid at time t. t up and P tdown These represent the up-adjustment and down-adjustment capacities of the energy storage terminal participating in the ancillary services of the power grid at time t, respectively. and These are the real-time up-capacity cost parameters and down-capacity cost parameters for the energy storage terminal participating in the ancillary services of the power grid at time t; and These represent the actual dispatch ratios of the energy storage terminal's up-shortage and down-shortage capacities participating in the grid's ancillary services at time t, predicted based on historical data; λ batt The cost of constructing and configuring energy storage devices; This represents the cyclical percentage of the energy storage lifecycle.

[0013] The dispatch capacity of energy storage participating in grid ancillary services includes both upward and downward dispatch capacity; the actual dispatch ratio of energy storage participating in grid ancillary services includes the actual dispatch ratio of upward and downward dispatch capacity; the power transmission cost parameters between energy storage and the load end include the output power cost parameters from the energy storage end to the load end and the input power cost parameters from the load end; the transmitted power between energy storage and the load end includes the output power from the energy storage end to the load end and the input power from the load end; the transmitted power between energy storage and the grid includes the output power from the energy storage end to the grid and the input power from the grid.

[0014] The constraints of the upper-level energy storage model include the interaction constraints between the energy storage terminal and the power grid, the interaction constraints between the energy storage terminal and the electricity load terminal, and the energy storage operation constraints, as detailed below:

[0015] a) Interaction constraints between energy storage and the power grid:

[0016]

[0017] Among them, P t BC1 and P t BD1 These represent the charging power and discharging power of the energy storage terminal interacting with the grid at time t, respectively. and These are the upper limits of the charging power and discharging power of the energy storage terminal interacting with the grid at time t, respectively. P is a Boolean variable representing the amount of electricity transferred from the energy storage terminal to the grid at time t, indicating the uniqueness of the input and output electricity at time t, i.e., they cannot occur simultaneously; B2G and These represent the lower and upper limits of the energy output from the energy storage terminal to the grid and the energy input from the grid at time t, respectively.

[0018] b) Interaction constraints between energy storage and electricity load:

[0019]

[0020] Among them, P t BC2 and P t BD2 These represent the charging power and discharging power of the energy storage terminal and the electrical load terminal at time t, respectively.

[0021] c) Energy storage operation constraints:

[0022]

[0023] Among them, E t and E t-1 Δt represents the state of charge level of the energy storage terminal at time t and time t-1, respectively; Δt is the optimization interval. E and E represent the highest and lowest state of charge levels of the energy storage terminal, respectively.

[0024] In step 1), the lower-level electrical load model is as follows:

[0025]

[0026]

[0027] Wherein, F4 is the cost of the input electricity from the grid to the power load terminal i at time t, F5 is the cost of the transmission electricity between the power load terminal i and the energy storage terminal at time t, and F6 is the cost of the ancillary services of the power load terminal i participating in the grid at time t. Let be the input electricity cost parameter of the power load terminal i from the power grid at time t; Let t be the power input from the power grid to the load terminal i at time t; and These are the output power cost parameters from the energy storage terminal to the power load terminal at time t and the input power cost parameters from the power load terminal to the energy storage terminal, respectively. and Let a be the output power from the energy storage terminal to the electrical load terminal i at time t, and the input power from the electrical load terminal to the energy storage terminal. i and b i These are the quadratic and linear coefficients of the ancillary service costs for electricity load i participating in the power grid; P i,t Let N be the total amount of electricity traded by load i participating in ancillary services at time t; N is the number of loads in the power grid. The transmitted electricity is the amount of electricity that the load terminals i and j participate in as ancillary services of the power grid at time t.

[0028] The constraints of the lower-level electricity load model include the interaction constraints between the electricity load end and the power grid and energy storage end, as well as the operational constraints of the electricity load end, as detailed below:

[0029] a) Interaction constraints between the electricity load end and the power grid and energy storage end:

[0030]

[0031] in, Let be a Boolean variable representing the transfer of electricity from the electrical load terminal i to the energy storage terminal at time t, indicating the uniqueness of the input and output electricity at time t; and These are the upper limits of the output power from the energy storage terminal to the electrical load terminal i and the input power from the electrical load terminal to the energy storage terminal, respectively. It is the upper limit of the power input from the power grid to the load terminal i at time t; and These are the upper limits of the charging and discharging power of the energy storage terminal and the electrical load terminal at time t, respectively.

[0032] b) Operating constraints at the electrical load end:

[0033]

[0034] in, and The state of charge levels of the electrical load terminal i at time t and time t-1 are respectively. and These represent the charging and discharging power of the electrical load terminal i at time t, respectively. and These are the charging and discharging efficiencies of the electrical load terminal i, respectively, under its state of charge. Let be the electricity consumption at load terminal i at time t; and These are the upper and lower limits of the state of charge at the electrical load terminal i, respectively; The state of charge at the end of charging of the electrical load terminal i at time t-dep; Let be a Boolean variable representing the charging and discharging action of the electrical load terminal i at time t, and let be the uniqueness of the charging and discharging at time t; This represents the grid connection status of the power load terminal i at time t, where 1 indicates grid connection and 0 indicates grid disconnection. and These are the upper limits of the charging and discharging power of the electrical load terminal i under its state of charge, respectively. and The indoor temperatures at the electrical load terminal i at time t and time t-1 are respectively. Let i be the outdoor temperature at the electrical load terminal i at time t-1; The working efficiency of the electrical load terminal i at time t; and These are the indoor thermal resistance and heat capacity of the electrical load terminal i, respectively; Let be the power consumption efficiency of the power load terminal i at time t. This represents the upper limit of the power consumption at the electrical load terminal i; and These represent the highest and lowest indoor temperatures at the electrical load terminal i, respectively.

[0035] The power consumption at the load end includes the charging and discharging power of the load end i under its state of charge, as well as the power consumption efficiency of the load end i at time t.

[0036] The grid dispatching system for energy storage participation scenarios of the present invention includes:

[0037] The data acquisition module is used to acquire the scheduling capacity and actual scheduling ratio of energy storage participating in the grid's ancillary services.

[0038] The model building module constructs an upper-level energy storage model and a lower-level electricity load model, thereby establishing a master-slave game system with the energy storage end on the demand side of the distribution network as the upper layer and the electricity load end on the demand side as the lower layer.

[0039] The grid dispatch module inputs the dispatch capacity of the energy storage terminal participating in the grid's ancillary services and the actual dispatch ratio into the upper-level energy storage model. After processing, it outputs the power transmission cost parameters of the energy storage terminal and the power load terminal, which are then input into the lower-level power load model. After processing, it outputs the transmitted power of the energy storage terminal and the power load terminal, which is then input into the upper-level energy storage model. This cycle continues until all variables in the master-slave game system reach steady-state values. The upper-level energy storage model outputs the transmitted power of the energy storage terminal and the grid as the dispatch quantity, while the lower-level power load model outputs the power consumption of the power load terminal and the power input from the grid as the dispatch quantity, thereby realizing the dispatch of the grid.

[0040] The electronic device of the present invention includes: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor invokes the program data to execute the method described above.

[0041] The present invention provides a computer-readable storage medium having program data stored thereon, characterized in that the program data, when executed by a processor, implements the method described above.

[0042] This invention overcomes the limitations of existing technologies by proposing a two-layer master-slave game model, achieving for the first time dynamic collaborative optimization of energy storage and electricity load-side resources. Through a multi-scenario integration mechanism (electrical energy, ancillary services, and dynamic degradation of energy storage) and dynamic parameter transmission in the master-slave game (transmission power cost parameters, scheduling power, etc.), it solves the problems of low resource utilization and insufficient model accuracy in existing technologies. Simultaneously, the combination of in-depth modeling of flexible resources on the electricity load side (such as the electric vehicle charge state equation and air conditioning thermodynamic constraints) with a point-to-point mechanism significantly improves the overall optimization and scheduling flexibility of the energy system, filling the technological gap in collaborative optimization and dynamic interaction.

[0043] The beneficial effects of this invention are:

[0044] 1. This invention fully considers various aspects of energy storage, including electrical energy, ancillary services, and degradation losses. It also minimizes the operating costs of the electricity load, primarily including electrical energy costs and point-to-point costs, which form a master-slave game relationship, leading to overall optimization.

[0045] 2. This invention fully considers the impact of real-time power adjustment on the model when energy storage participates in ancillary services. It determines the ratio of the actual power adjustment to the reported power adjustment through historical data and incorporates it into the model, making the model more accurate and complete.

[0046] 3. This invention fully considers the resources of the electricity load, including flexible resources such as air conditioners and electric vehicles, and has carried out detailed modeling of their operation, which is of great significance for improving the overall flexibility of the resources on the electricity load side.

[0047] 4. The decision-maker in the upper-level model of this invention is energy storage, which takes into account electrical energy, ancillary services, and its own degradation losses, and fully considers the constraints related to interaction with the power grid and the electricity load side, as well as operational constraints. In particular, it considers the impact of real-time power adjustments made by energy storage in ancillary services, making the model more reasonable and accurate. The decision-maker in the lower-level model is the electricity load, whose operating costs consider electrical energy and point-to-point connections. The model also considers flexible resources (air conditioning, electric vehicles) and models their operating modes, fully utilizing the flexible scheduling potential of electricity load-side resources. Attached Figure Description

[0048] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0049] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0050] like Figure 1 As shown, the grid dispatching method of the present invention in the scenario of energy storage participation is as follows:

[0051] Step 1) Establish a master-slave game system with the energy storage end on the demand side of the distribution network as the upper layer and the electricity load end on the demand side as the lower layer. The master-slave game system includes an upper-layer energy storage model and a lower-layer electricity load model.

[0052] Step 2) Input the dispatch capacity of the energy storage terminal participating in the grid's ancillary services and the actual dispatch ratio into the upper-level energy storage model. After processing, output the power transmission cost parameters of the energy storage terminal and the power load terminal, and then input them into the lower-level power load model. After processing, output the transmitted power of the energy storage terminal and the power load terminal, and then input them into the upper-level energy storage model continuously. The cost can be specifically measured in terms of power. Until the variables in the master-slave game system reach a steady state value, the upper-level energy storage model outputs the transmitted power of the energy storage terminal and the grid as the dispatch quantity, and the lower-level power load model outputs the power consumption of the power load terminal and the power input from the grid as the dispatch quantity, so as to realize the dispatch of the grid.

[0053] The upper-level energy storage model is as follows:

[0054] maxF1+F2-F3

[0055]

[0056] Where F1 and F2 are the input costs of the energy storage terminal participating in the power grid and the ancillary services of the power grid, respectively, and F3 is the degradation cost of the energy storage terminal; T is the optimization period. In specific implementation, the optimization period is one day, the optimization interval Δt is 1 hour, so T is 24 hours. and P represents the energy cost parameters of the energy storage terminal outputting electricity to the grid and the energy cost parameters of the energy storage terminal inputting electricity from the grid at time t, respectively. t B2G and P t G2B These represent the output power from the energy storage terminal to the grid and the input power from the energy storage terminal to the grid at time t, respectively, in kW; N is the number of electrical load terminals within the grid; and These are the output power cost parameters from the energy storage terminal to the power load terminal at time t and the input power cost parameters from the power load terminal to the energy storage terminal, respectively. and These represent the output power from the energy storage terminal to the electrical load terminal i at time t and the input power from the electrical load terminal to the energy storage terminal, respectively, in kW; P represents the day-ahead cost parameter for energy storage participating in ancillary services of the power grid at time t. t up and P t down These represent the up-regulation and down-regulation capacities of the energy storage terminal participating in the ancillary services of the power grid at time t, respectively, in kW; and These are the real-time up-capacity cost parameters and down-capacity cost parameters for the energy storage terminal participating in the ancillary services of the power grid at time t; and These represent the actual dispatch ratios (in percent) of the energy storage capacity participating in ancillary services of the power grid at time t, predicted based on historical data; λ batt The cost of constructing and configuring energy storage devices; This represents the cyclical percentage of the energy storage lifecycle.

[0057] The dispatch capacity of energy storage participating in grid ancillary services includes both upward and downward dispatch capacity; the actual dispatch ratio of energy storage participating in grid ancillary services includes the actual dispatch ratio of upward and downward dispatch capacity; the power transmission cost parameters between energy storage and the load end include the output power cost parameters from the energy storage end to the load end and the input power cost parameters from the load end; the transmitted power between energy storage and the load end includes the output power from the energy storage end to the load end and the input power from the load end; the transmitted power between energy storage and the grid includes the output power from the energy storage end to the grid and the input power from the grid.

[0058] Cycle percentage of the life cycle of energy storage Specifically as follows:

[0059]

[0060] Among them, EFC t L represents the number of cycles the energy storage unit completes within a unit optimization time period at time t. cyc The entire lifecycle of the energy storage device is measured in cycles; η C and η D These represent the charging efficiency and discharging efficiency of the energy storage terminal, respectively, in %; P t BC1 and P t BD1 P represents the charging and discharging power of the energy storage terminal interacting with the grid at time t, respectively, in kW; t BC2 and P t BD2 E represents the charging and discharging power of the energy storage terminal and the electrical load terminal at time t, respectively, in kW; cap It is the energy capacity limit of the energy storage end, in kWh.

[0061] The constraints of the upper-level energy storage model include the interaction constraints between the energy storage terminal and the power grid, the interaction constraints between the energy storage terminal and the electricity load terminal, and the energy storage operation constraints, as detailed below:

[0062] a) Interaction constraints between energy storage and the power grid:

[0063]

[0064] Among them, P t BC1 and P t BD1 These represent the charging power and discharging power of the energy storage terminal interacting with the grid at time t, respectively. and These are the upper limits of the charging and discharging power of the energy storage terminal interacting with the grid at time t, respectively, in kW; This is a Boolean variable representing the amount of electricity transferred from the energy storage terminal to the grid at time t, indicating the uniqueness of the input and output electricity at time t, i.e., they cannot occur simultaneously. P B2G and These represent the lower and upper limits of the energy output from the energy storage terminal to the grid and the energy input from the grid at time t, respectively, in kW.

[0065] When energy storage interacts with the grid at time t, the power balance constraints that the charging and discharging power need to meet consist of the power transmitted to the grid and the actual ancillary service power provided. The power constraints for the energy storage to provide up and down ancillary services to the grid at time t are consistent with the grid's power transmission behavior.

[0066] b) Interaction constraints between energy storage and electricity load:

[0067]

[0068]

[0069] Among them, P t BC2 and P t BD2 These represent the charging power and discharging power of the energy storage terminal and the electrical load terminal at time t, respectively.

[0070] At time t, when energy storage interacts with the electricity load side, the power balance constraint that the charging and discharging power needs to satisfy is composed of the aggregated power of the electricity transferred to all electricity load sides. The protection constraint ensures that the charging and discharging power do not occur simultaneously when energy storage interacts with the electricity load side.

[0071] c) Energy storage operation constraints:

[0072]

[0073] Among them, E t and E t-1Δt represents the state of charge level of the energy storage terminal at time t and t-1, respectively, in kWh; Δt is the optimization interval. E and E represent the highest and lowest state of charge levels of the energy storage device, respectively, in kWh.

[0074] The specific electrical load model for the lower level is as follows:

[0075]

[0076]

[0077] Wherein, F4 is the cost of the input electricity from the grid to the power load terminal i at time t, F5 is the cost of the transmission electricity between the power load terminal i and the energy storage terminal at time t, and F6 is the cost of the ancillary services of the power load terminal i participating in the grid at time t. Let be the input electricity cost parameter of the power load terminal i from the power grid at time t; Let t be the power input from the power grid to the load terminal i at time t; and These are the output power cost parameters from the energy storage terminal to the power load terminal at time t and the input power cost parameters from the power load terminal to the energy storage terminal, respectively. and Let a be the output power from the energy storage terminal to the electrical load terminal i at time t, and the input power from the electrical load terminal to the energy storage terminal. i and b i These are the quadratic and linear coefficients of the ancillary service costs for electricity load i participating in the power grid; P i,t The total electricity traded at time t for load i participating in ancillary services is expressed in kW; N is the number of loads in the power grid. The amount of electricity transmitted by load terminals i and j to participate in the ancillary services of the power grid at time t is expressed in kW.

[0078] The constraints of the lower-level electricity load model include the interaction constraints between the electricity load end and the power grid and energy storage end, as well as the operational constraints of the electricity load end, as detailed below:

[0079] a) Interaction constraints between the electricity load end and the power grid and energy storage end:

[0080]

[0081] in, Let be a Boolean variable representing the transfer of electricity from the electrical load terminal i to the energy storage terminal at time t, indicating the uniqueness of the input and output electricity at time t; and These are the upper limits of the output power from the energy storage terminal to the electrical load terminal i and the input power from the electrical load terminal to the energy storage terminal, respectively, in kW; It is the upper limit of the electrical power input from the power grid to the electrical load terminal i at time t, in kW; and These are the upper limits of the charging and discharging power of the energy storage terminal and the electrical load terminal at time t, respectively, in kW.

[0082] b) Operating constraints at the electrical load end:

[0083]

[0084] in, and These are the state-of-charge levels of electric vehicles within load i at time t and time t-1, respectively, in kWh. and These are the charging and discharging power of the electric vehicle at the electrical load terminal i at time t, respectively, in kW; and The charging and discharging efficiencies of the electric vehicle within the electrical load terminal i are respectively, in %; The electricity consumption of electric vehicles within the load terminal i at time t is expressed in kWh. and These are the upper and lower limits of the state of charge of electric vehicles within the electrical load terminal i, respectively, in kWh; The state of charge of an electric vehicle at the load end i at time t-dep when it leaves the charging pile is the end of charging, expressed in kWh. Let be a Boolean variable representing the charging and discharging actions of electric vehicles within the electrical load terminal i at time t, and let represent the uniqueness of charging and discharging at time t. The grid connection status of electric vehicles within the power load terminal i at time t, where 1 indicates grid connection and 0 indicates grid disconnection; and These are the upper limits of the charging and discharging power of the electric vehicle within the electrical load terminal i, respectively, in kW; and The indoor temperatures at the electrical load terminal i at time t and time t-1 are respectively, in °C. The outdoor temperature at the electrical load terminal i at time t-1 is expressed in °C. The efficiency of the air conditioner at electrical load terminal i at time t is expressed in %; and These are the indoor thermal resistance and heat capacity of the electrical load terminal i, respectively, with units of ℃ / kW and kW / ℃; Let be the power efficiency of the air conditioner at load i at time t, in kW. This represents the upper limit of the power consumption of the air conditioner at the electrical load end i. and These are the highest and lowest indoor temperatures at electrical load terminal i, respectively, in °C.

[0085] The power consumption at the load end includes the charging and discharging power of the electric vehicle in load end i and the power consumption efficiency of the air conditioner at load end i at time t.

[0086] It also includes transmission constraints and power balance constraints, as detailed below:

[0087] Transmission constraints:

[0088]

[0089] in, The upper limit of the amount of electricity transmitted by load terminals i and j to participate in the ancillary services of the power grid, in kW; Let t be the amount of electricity transmitted between load terminals i and j at time t to participate in the ancillary services of the power grid.

[0090] Power balance constraints:

[0091]

[0092] in, and These represent the rooftop photovoltaic output and non-flexible load at time t, respectively, with units of kW.

[0093] This invention also designs a power grid dispatching system for scenarios involving energy storage, including a data acquisition module, a model building module, and a power grid dispatching module. The data acquisition module is used to acquire the dispatching capacity and actual dispatch ratio of the energy storage terminal participating in the ancillary services of the power grid. The model building module constructs an upper-level energy storage model and a lower-level electricity load model, thereby establishing a master-slave game system with the energy storage terminal on the demand side of the distribution network as the upper layer and the electricity load terminal on the demand side as the lower layer. The power grid dispatching module inputs the dispatching capacity and actual dispatch ratio of the energy storage terminal participating in the ancillary services of the power grid into the upper-level energy storage model, processes it, outputs the power transmission cost parameters of the energy storage terminal and the electricity load terminal, and then inputs them into the lower-level electricity load model. After processing, it outputs the transmitted power of the energy storage terminal and the electricity load terminal and then inputs it into the upper-level energy storage model. This cycle continues until the variables in the master-slave game system reach steady-state values. The upper-level energy storage model outputs the transmitted power of the energy storage terminal and the power grid as the dispatch quantity, and the lower-level electricity load model outputs the power consumption of the electricity load terminal and the power input from the power grid as the dispatch quantity, so as to realize the dispatching of the power grid.

[0094] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented using various computer languages. This application is described with flowcharts of methods, systems, and computer program products according to embodiments of this application.

[0095] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, this invention is intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0096] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if these modifications and variations of this application fall within the scope of the equivalent technology of this invention, this application also intends to include these modifications and variations.

Claims

1. A power grid dispatching method in an energy storage participation scenario, characterized in that, include: Step 1) Establish a master-slave game system with the energy storage end on the demand side of the distribution network as the upper layer and the electricity load end on the demand side as the lower layer. The master-slave game system includes an upper-layer energy storage model and a lower-layer electricity load model. Step 2) Input the dispatch capacity of the energy storage terminal participating in the grid's ancillary services and the actual dispatch ratio into the upper-level energy storage model. After processing, output the power transmission cost parameters of the energy storage terminal and the power load terminal, and then input them into the lower-level power load model. After processing, output the transmitted power of the energy storage terminal and the power load terminal, and then input them into the upper-level energy storage model. This cycle continues until all variables in the master-slave game system reach steady-state values. The upper-level energy storage model outputs the transmitted power of the energy storage terminal and the grid as the dispatch quantity, and the lower-level power load model outputs the power consumption of the power load terminal and the power input from the grid as the dispatch quantity, so as to realize the dispatch of the grid.

2. The method of claim 1, wherein: In step 1), the upper-layer energy storage model is as follows: maxF1+F2-F3 Wherein, F1 and F2 are input cost of energy storage end participating in power grid and participating in auxiliary service of power grid respectively, F3 is degradation cost of energy storage end; T is optimization period; λ t B2G and λ t G2B are output power cost parameter and input power cost parameter of energy storage end to power grid at t moment respectively; P t B2G and P t G2B are output power of energy storage end to power grid and input power of energy storage end from power grid at t moment respectively; N is the number of power load end in power grid; λ t B2H and λ t H2B are output power cost parameter and input power cost parameter of energy storage end to power load end at t moment respectively; and are output power of energy storage end to power load end i and input power of energy storage end from power load end at t moment respectively; is day-ahead cost parameter of energy storage end participating in auxiliary service of power grid at t moment; P t up and P t down are up-regulation capacity and down-regulation capacity of energy storage end participating in auxiliary service of power grid at t moment respectively; and are real-time up-regulation capacity cost parameter and down-regulation capacity cost parameter of energy storage end participating in auxiliary service of power grid at t moment respectively; and are actual scheduling proportion of up-regulation capacity and down-regulation capacity of energy storage end participating in auxiliary service of power grid at t moment respectively; λ batt is construction configuration cost of energy storage end; is cycle proportion of life cycle of energy storage end; The dispatch capacity of energy storage participating in grid ancillary services includes both upward and downward dispatch capacity; the actual dispatch ratio of energy storage participating in grid ancillary services includes the actual dispatch ratio of upward and downward dispatch capacity; the power transmission cost parameters between energy storage and the load end include the output power cost parameters from the energy storage end to the load end and the input power cost parameters from the load end; the transmitted power between energy storage and the load end includes the output power from the energy storage end to the load end and the input power from the load end; the transmitted power between energy storage and the grid includes the output power from the energy storage end to the grid and the input power from the grid.

3. The method of claim 2, wherein: The constraints of the upper-level energy storage model include the interaction constraints between the energy storage terminal and the power grid, the interaction constraints between the energy storage terminal and the electricity load terminal, and the energy storage operation constraints, as detailed below: a) Interaction constraints between energy storage and the power grid: wherein P t BC1 and P t BD1 Pcharge(t) and Pdischarge(t) are the charging power and discharging power of the energy storage end interacting with the power grid at time t, respectively, and Pcharge(t) and Pdischarge(t) are the upper limit values of the charging power and discharging power of the energy storage end interacting with the power grid at time t, respectively; Ptrans(t) is a Boolean variable of the transmission power action of the energy storage end to the power grid at time t; P B2G and Pout(t) and Pin(t) are the lower limit value and upper limit value of the output power and input power of the energy storage end to / from the power grid at time t, respectively. b) Interaction constraints between energy storage and electricity load: wherein P t BC2 and P t BD2 are the charging and discharging power exchanged between the energy storage end and the power consumption load end at time t, respectively. c) Energy storage operation constraints: wherein E t and E t-1 are the state-of-charge levels of the energy storage at time t and t-1, respectively; and Δt is the optimization interval. and E are the highest and lowest state-of-charge levels of the energy storage, respectively.

4. The method of claim 1, wherein: In step 1), the lower-level electrical load model is as follows: Where F4 is the cost of the electricity input from the grid to load i at time t, F5 is the cost of the electricity transmission between load i and the energy storage unit at time t, and F6 is the cost of the ancillary services provided by load i to the grid at time t; λ t G2H Let be the input electricity cost parameter of the power load terminal i from the power grid at time t; Let λ be the power input from the power grid to the load terminal i at time t; t B2H and λ t H2B These are the output power cost parameters from the energy storage terminal to the power load terminal at time t and the input power cost parameters from the power load terminal to the energy storage terminal, respectively. and Let a be the output power from the energy storage terminal to the electrical load terminal i at time t, and the input power from the electrical load terminal to the energy storage terminal. i and b i These are the quadratic and linear coefficients of the ancillary service costs for electricity load i participating in the power grid; P i,t Let N be the total electricity volume traded by load i at time t for ancillary services; N is the number of loads in the power grid. The transmitted electricity is the amount of electricity that the load terminals i and j participate in as ancillary services of the power grid at time t.

5. The method of claim 4, wherein: The constraints of the lower-level electricity load model include the interaction constraints between the electricity load end and the power grid and energy storage end, as well as the operational constraints of the electricity load end, as detailed below: a) Interaction constraints between the electricity load end and the power grid and energy storage end: wherein, is a Boolean variable of the transmission of the electric quantity from the power consumption end i to the energy storage end at time t; and are the upper limit values of the output electric quantity of the energy storage end to the power consumption end i and the input electric quantity of the energy storage end from the power consumption end, respectively; is the upper limit value of the input electric quantity power of the power consumption end i from the power grid at time t; and are the upper limit values of the charging power and the discharging power exchanged between the energy storage end and the power consumption end at time t, respectively; b) Operating constraints at the electrical load end: wherein, and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; is the power consumption amount of the power consumption load end i at time t; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; is the state-of-charge of the power consumption load end i at time t-dep when the charging ends; is the Boolean variable of the charging and discharging action of the power consumption load end i at time t; is the grid-connected state of the power consumption load end i at time t; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; is the outdoor temperature at the power consumption load end i at time t-1; is the working efficiency of the power consumption load end i at time t; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; is the power consumption efficiency of the power consumption load end i at time t, is the upper limit value of the power consumption of the power consumption load end i; and SoC(t) and SoC(t-1) are the state-of-charge levels of the power consumption load end i at time t and time t-1, respectively; The power consumption at the load end includes the charging and discharging power of the load end i under its state of charge, as well as the power consumption efficiency of the load end i at time t.

6. A power grid dispatching system under energy storage participation scenario, characterized in that, include: The data acquisition module is used to acquire the dispatch capacity and actual dispatch ratio of energy storage participating in the grid's ancillary services. The model building module constructs an upper-layer energy storage model and a lower-layer electricity load model, thereby establishing a master-slave game system with the energy storage end on the demand side of the distribution network as the upper layer and the electricity load end on the demand side as the lower layer. The power grid dispatching module inputs the dispatching capacity of the energy storage end participating in the auxiliary service of the power grid and the actual dispatching ratio into the upper energy storage model, outputs the power transmission cost parameters of the energy storage end and the power consumption load end, and then inputs them into the lower power consumption load model, and then inputs the transmission power of the energy storage end and the power consumption load end after processing into the upper energy storage model, and the cycle is repeated until the variables in the master-slave game system reach the steady state value, the upper energy storage model outputs the transmission power of the energy storage end and the power grid as the dispatching quantity, and the lower power consumption load model outputs the power consumption power of the power consumption load end and the input power from the power grid as the dispatching quantity, so as to realize the dispatching of the power grid.

7. An electronic device, comprising: Comprise: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor invokes the program data to execute the method of any one of claims 1-5.

8. A computer readable storage medium having stored thereon program data, wherein, The program data is executed by the processor to implement the method of any one of claims 1-5.

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