Power distribution area real-time scheduling method and device based on micro pumped storage power station

Abstract

The invention relates to the technical field of power grid dispatching, and particularly provides a power distribution area real-time dispatching method and device based on a micro pumped storage power station, and the method comprises the steps: determining an additional constraint condition based on the reservoir sharing condition of the micro pumped storage power station of an area, adding the additional constraint condition into a power distribution network transformer area real-time scheduling model corresponding to the transformer area; solving the power distribution network transformer area real-time scheduling model corresponding to the transformer area to obtain an optimization result; and taking the optimization result as a real-time scheduling scheme of the transformer area. According to the technical scheme provided by the invention, the energy supply relation of multiple transformer areas is effectively changed, a single energy mutual aid mode is changed into an electricity and water two-path energy mutual aid mode, the optimal control of the whole system is formed, and the method has important significance on the stability and economical efficiency of local power grid operation.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid dispatching, and in particular to a real-time dispatching method and device for a distribution substation based on a micro pumped storage power station. Background Art

[0002] As wind and photovoltaic power enter an era of grid parity, the penetration of renewable energy generation is accelerating, and the traditional power system will gradually transform into a new power system dominated by renewable energy. Due to the high intermittent and random nature of wind and photovoltaic power generation, the large-scale integration of renewable energy into the grid will seriously affect the stability of the power grid. Energy storage technology is generally considered an effective solution to this problem.

[0003] The main energy storage methods used in power systems include physical and chemical energy storage. Pumped-storage power stations, a type of physical energy storage, are highly technically mature and offer multiple functions, including peak-to-valley shifting, frequency regulation, phase modulation, and black start. Lithium-ion batteries, a type of electrochemical energy storage, are a highly mature and widely used energy storage technology. However, the pumps and turbines of traditional pumped-storage power stations cannot operate normally under low operating conditions, and pumped-storage units cannot quickly switch between storage and power generation during real-time daily scheduling, which impacts the absorption of renewable energy. Therefore, a real-time scheduling method for distribution substations based on micro-pumped-storage power stations is urgently needed. Summary of the Invention

[0004] In order to overcome the above-mentioned defects, the present invention proposes a real-time dispatching method and device for a distribution substation based on a micro pumped storage power station.

[0005] In a first aspect, a real-time scheduling method for a distribution area based on a micro pumped storage power station is provided. The real-time scheduling method for a distribution area based on a micro pumped storage power station comprises:

[0006] Determine additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and add the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation;

[0007] Solve the real-time dispatch model of the distribution network corresponding to the substation to obtain the optimization result;

[0008] Using the optimization result as a real-time dispatching plan for the substation;

[0009] Among them, the real-time dispatching model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching and its corresponding constraints.

[0010] Preferably, the optimization results include: photovoltaic power generation power, wind power generation power, water pump pumped storage power, turbine power generation power, water pump working state variable, turbine working state variable, total pumped storage power, upstream reservoir water storage capacity, downstream reservoir water storage capacity, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variable, energy storage battery discharging state variable, energy storage battery total power, energy storage battery capacity, grid injection power, change value of grid injection power, and total power supplied by the system to the load.

[0011] Preferably, the reservoir sharing situation includes: the micro pumped storage power stations in two substations share a downstream reservoir or the micro pumped storage power stations in two substations share an upstream reservoir.

[0012] Furthermore, when the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows:

[0013]

[0014] In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the i-th station at time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumping storage power of the i-th station at time k; is the turbine power generation at time k in the i-th station, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the i-th station, is the turbine power generation efficiency of the i-th substation, and Δt is the regulation time interval.

[0015] Furthermore, when the micro pumped storage power stations in two substations share a common upstream reservoir, the additional constraints are as follows:

[0016]

[0017] In the above formula, V H (k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the i-th station at time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

[0018] Furthermore, the first objective function is as follows:

[0019]

[0020] In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th station at time k+j, is the photovoltaic power generation power of the i-th station at time k+j, is the maximum wind power generation power at the i-th station k+j, is the wind power generation power of the i-th station at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied to the load by the system at time k+j in the i-th substation, and t is the current time.

[0021] Furthermore, the second objective function is as follows:

[0022]

[0023] In the above formula, J2 is the second objective function value, is the wind power generation capacity dispatched by the system at time k+j in the i-th area, is the photovoltaic power generation power dispatched by the system at time k+j in the i-th station, is the total pumped storage power dispatched by the system at time k+j in the i-th station, is the total pumped storage power of the i-th station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th area, is the energy storage battery energy of the i-th station at time k+j, is the grid injection power dispatched by the system at time k+j in the i-th substation, is the change value of the grid injection power dispatched by the system at time k+j in the i-th substation, is the change in power injected into the grid at time k+j in the ith substation, The total power of the system supply load at the i-th substation at time k+j is dispatched by the system the day before.

[0024] Furthermore, the mathematical model of the constraint condition is as follows:

[0025]

[0026] In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power at the i-th station at time k, is the maximum photovoltaic power generation power at the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the i-th substation at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the i-th substation at time k in the history day, is the maximum water storage capacity of the upstream reservoir of the ith station in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith substation in the historical day, is the energy state of the energy storage battery in the i-th station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the i-th station, is the maximum energy of the energy storage battery in the i-th station, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power generated by the reservoir at time k in the i-th station, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change in power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

[0027] Furthermore, the or 1, or 1 and when When the pumped storage unit at time k in the i-th station stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the or 1, or 1, when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

[0028] In a second aspect, a real-time dispatching device for a distribution area based on a micro pumped storage power station is provided. The real-time dispatching device for a distribution area based on a micro pumped storage power station comprises:

[0029] The first analysis module is used to determine additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and add the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation;

[0030] The second analysis module is used to solve the real-time dispatch model of the distribution network corresponding to the substation to obtain the optimization result;

[0031] A scheduling module, configured to use the optimization result as a real-time scheduling plan for the substation;

[0032] Among them, the real-time dispatching model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching and its corresponding constraints.

[0033] Preferably, the optimization results include: photovoltaic power generation power, wind power generation power, water pump pumped storage power, turbine power generation power, water pump working state variable, turbine working state variable, total pumped storage power, upstream reservoir water storage capacity, downstream reservoir water storage capacity, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variable, energy storage battery discharging state variable, energy storage battery total power, energy storage battery capacity, grid injection power, change value of grid injection power, and total power supplied by the system to the load.

[0034] Preferably, the reservoir sharing situation includes: the micro pumped storage power stations in two substations share a downstream reservoir or the micro pumped storage power stations in two substations share an upstream reservoir.

[0035] Furthermore, when the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows:

[0036]

[0037] In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the i-th station at time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumping storage power of the i-th station at time k; is the turbine power generation at time k in the i-th station, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the i-th station, is the turbine power generation efficiency of the i-th substation, and Δt is the regulation time interval.

[0038] Furthermore, when the micro pumped storage power stations in two substations share a common upstream reservoir, the additional constraints are as follows:

[0039]

[0040] In the above formula, V H (k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the i-th station at time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

[0041] Furthermore, the first objective function is as follows:

[0042]

[0043] In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th station at time k+j, is the photovoltaic power generation power of the i-th station at time k+j, is the maximum wind power generation power at the i-th station k+j, is the wind power generation power of the i-th station at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied to the load by the system at time k+j in the i-th substation, and t is the current time.

[0044] Furthermore, the second objective function is as follows:

[0045]

[0046] In the above formula, J2 is the second objective function value, is the wind power generation capacity dispatched by the system at time k+j in the i-th area, is the photovoltaic power generation power dispatched by the system at time k+j in the i-th station, is the total pumped storage power dispatched by the system at time k+j in the i-th station, is the total pumped storage power of the i-th station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th area, is the energy storage battery energy of the i-th station at time k+j, is the grid injection power dispatched by the system at time k+j in the i-th substation, is the change value of the grid injection power dispatched by the system at time k+j in the i-th substation, is the change in power injected into the grid at time k+j in the ith substation, The total power of the system supply load at the i-th substation at time k+j is dispatched by the system the day before.

[0047] Furthermore, the mathematical model of the constraint condition is as follows:

[0048]

[0049] In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power at the i-th station at time k, is the maximum photovoltaic power generation power at the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the i-th substation at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the i-th substation at time k in the history day, is the maximum water storage capacity of the upstream reservoir of the ith station in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith substation in the historical day, is the energy state of the energy storage battery in the i-th station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the i-th station, is the maximum energy of the energy storage battery in the i-th station, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power generated by the reservoir at time k in the i-th station, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change in power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

[0050] Furthermore, the or 1, or 1 and when When the pumped storage unit at time k in the i-th station stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the or 1, or 1, when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

[0051] In a third aspect, a computer device is provided, comprising: one or more processors;

[0052] The processor is configured to execute one or more programs;

[0053] When the one or more programs are executed by the one or more processors, the real-time scheduling method for distribution station areas based on micro pumped storage power stations is implemented.

[0054] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed, the real-time scheduling method of the distribution station area based on the micro pumped storage power station is implemented.

[0055] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0056] The present invention provides a method and device for real-time dispatching of distribution network substations based on micro pumped storage power stations, comprising: determining additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation area, and adding the additional constraints to the real-time dispatching model of the distribution network substation area corresponding to the substation area; solving the real-time dispatching model of the distribution network substation area corresponding to the substation area to obtain an optimization result; using the optimization result as the real-time dispatching plan of the substation area; wherein the real-time dispatching model of the distribution network substation area corresponding to the substation area includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching, and its corresponding constraints. The technical solution provided by the present invention effectively changes the energy supply relationship of multiple substations, from a single energy mutual assistance mode to a mode of mutual assistance of electricity and water energy, forming the optimal control of the entire system, which will be of great significance to the stability and economy of the local power grid operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of the main steps of a real-time dispatching method for a distribution area based on a micro pumped storage power station according to an embodiment of the present invention;

[0058] Figure 2 It is a schematic diagram of the shared reservoir operation mode of a micro pumped storage power station according to an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0061] As disclosed in the background technology, as wind power and photovoltaic power enter an era of grid parity, the penetration rate of renewable energy generation is accelerating, and the traditional power system will gradually transform into a new power system dominated by renewable energy. Due to the high intermittent and random nature of wind and photovoltaic power generation, the large-scale integration of renewable energy into the grid will seriously affect the stability of the power grid. Energy storage technology is generally considered an effective solution to this problem.

[0062] The main energy storage methods used in power systems include physical and chemical energy storage. Pumped-storage power stations, a type of physical energy storage, are highly technically mature and offer multiple functions, including peak-to-valley shifting, frequency regulation, phase modulation, and black start. Lithium-ion batteries, a type of electrochemical energy storage, are a highly mature and widely used energy storage technology. However, the pumps and turbines of traditional pumped-storage power stations cannot operate normally under low operating conditions, and pumped-storage units cannot quickly switch between storage and power generation during real-time daily scheduling, which impacts the absorption of renewable energy. Therefore, a real-time scheduling method for distribution substations based on micro-pumped-storage power stations is urgently needed.

[0063] In order to improve the above-mentioned problems, the present invention provides a method and device for real-time dispatching of distribution network areas based on micro pumped storage power stations, comprising: determining additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the area, and adding the additional constraints to the real-time dispatching model of the distribution network area corresponding to the area; solving the real-time dispatching model of the distribution network area corresponding to the area to obtain an optimization result; using the optimization result as the real-time dispatching scheme of the area; wherein the real-time dispatching model of the distribution network area corresponding to the area includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching, and its corresponding constraints. The technical solution provided by the present invention effectively changes the energy supply relationship of multiple areas, from a single energy mutual assistance mode to a mode of mutual assistance of electricity and water energy, forming the optimal control of the overall system, which will be of great significance to the stability and economy of the local power grid operation. The above solution is elaborated in detail below.

[0064] Example 1

[0065] See attached Figure 1 , Figure 1 FIG1 is a flow chart of the main steps of a real-time dispatching method for a distribution area based on a micro pumped storage power station according to an embodiment of the present invention. Figure 1 As shown, the real-time dispatching method for distribution area based on micro pumped storage power station in the embodiment of the present invention mainly includes the following steps:

[0066] Step S101: determining additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and adding the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation;

[0067] Step S102: solving the real-time dispatch model of the distribution network corresponding to the substation to obtain an optimization result;

[0068] Step S103: Using the optimization result as a real-time scheduling plan for the substation;

[0069] The real-time dispatch model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of minimizing the abandonment of wind power, photovoltaic power generation, and load shedding, a second objective function with the goal of maximizing the fit between intraday dispatch and day-ahead dispatch, and their corresponding constraints. The optimization results include: photovoltaic power generation power, wind power generation power, water pump pumped storage power, turbine power generation power, water pump operating state variables, turbine operating state variables, total pumped storage power, upstream reservoir water storage capacity, downstream reservoir water storage capacity, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variables, energy storage battery discharging state variables, total energy storage battery power, energy storage battery capacity, grid injection power, change in grid injection power, and total power supplied to the system load.

[0070] In this example, Figure 2 As shown, the reservoir sharing situation includes: two micro-pumped storage power stations in different areas share a downstream reservoir, or two micro-pumped storage power stations in different areas share a upstream reservoir. At the same time, energy storage batteries are used to achieve energy conversion and energy integration and scheduling between different areas.

[0071] In one embodiment, when the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows:

[0072]

[0073] In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the i-th station at time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumping storage power of the i-th station at time k; is the turbine power generation at time k in the i-th station, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the i-th station, is the turbine power generation efficiency of the i-th substation, and Δt is the regulation time interval.

[0074] In one embodiment, when the micro pumped storage power stations in two substations share a common upstream reservoir, the additional constraints are as follows:

[0075]

[0076] In the above formula, V H(k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the i-th station at time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

[0077] In one embodiment, the first objective function is as follows:

[0078]

[0079] In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th station at time k+j, is the photovoltaic power generation power of the i-th station at time k+j, is the maximum wind power generation power at the i-th station k+j, is the wind power generation power of the i-th station at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied to the load by the system at time k+j in the i-th substation, and t is the current time.

[0080] In one embodiment, the second objective function is as follows:

[0081]

[0082] In the above formula, J2 is the second objective function value, is the wind power generation capacity dispatched by the system at time k+j in the i-th area, is the photovoltaic power generation power dispatched by the system at time k+j in the i-th station, is the total pumped storage power dispatched by the system at time k+j in the i-th station, is the total pumped storage power of the i-th station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th area, is the energy storage battery energy of the i-th station at time k+j, is the grid injection power dispatched by the system at time k+j in the i-th substation, is the change value of the grid injection power dispatched by the system at time k+j in the i-th substation, is the change in power injected into the grid at time k+j in the ith substation, The total power of the system supply load at the i-th substation at time k+j is dispatched by the system the day before.

[0083] In one embodiment, the mathematical model of the constraint condition is as follows:

[0084]

[0085]

[0086] In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power at the i-th station at time k, is the maximum photovoltaic power generation power at the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the i-th substation at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the i-th substation at time k in the history day, is the maximum water storage capacity of the upstream reservoir of the ith station in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith substation in the historical day, is the energy state of the energy storage battery in the i-th station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the i-th station, is the maximum energy of the energy storage battery in the i-th station, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power generated by the reservoir at time k in the i-th station, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change in power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

[0087] In one embodiment, the or 1, or 1 and when When the pumped storage unit at time k in the i-th station stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the or 1, or 1, when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

[0088] In a specific implementation, the Whale Intelligent Optimization Algorithm is used to obtain the real-time optimal control instructions for wind, solar, energy storage batteries, and pumped storage in the distribution area under the reservoir sharing mode of the micro pumped storage power station, so as to achieve the goal of minimizing the abandoned wind and photovoltaic power generation power, minimizing the occupancy of transmission lines, maximizing the compliance with the day-ahead scheduling, and minimizing the load shedding.

[0089] The optimization variables include the photovoltaic power generation power at time k in the i-th station Wind power generation Pumped storage power Turbine power generation Pump working state variables Turbine operating state variables Total pumped storage power Water storage capacity of upstream reservoirs Water storage capacity of downstream reservoirs Energy storage battery charging power Energy storage battery discharge power Energy storage battery charge state variables Energy storage battery discharge state variables Total power of energy storage battery Energy storage battery capacity Grid injection power Changes in grid injected power The total power supplied by the system to the load in The water pump stops running. When the water pump starts running; When the turbine generator set stops running, When the turbine generator set starts running; Non-continuous variables, when Time to take when Pick Similarly Time to take when Pick When the energy storage battery stops charging, The energy storage battery starts charging; When the energy storage battery stops discharging, When the energy storage battery begins to discharge; Non-continuous variables, when Time to take when Pick Similarly Time to take when Pick Place N whales in the B-dimensional space composed of the above variables.

[0090] Example 2

[0091] Based on the same inventive concept, the present invention also provides a real-time dispatching device for a distribution area based on a micro pumped storage power station. The real-time dispatching device for a distribution area based on a micro pumped storage power station comprises:

[0092] The first analysis module is used to determine additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and add the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation;

[0093] The second analysis module is used to solve the real-time dispatch model of the distribution network corresponding to the substation to obtain the optimization result;

[0094] A scheduling module, configured to use the optimization result as a real-time scheduling plan for the substation;

[0095] Among them, the real-time dispatching model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching and its corresponding constraints.

[0096] Preferably, the optimization results include: photovoltaic power generation power, wind power generation power, water pump pumped storage power, turbine power generation power, water pump working state variable, turbine working state variable, total pumped storage power, upstream reservoir water storage capacity, downstream reservoir water storage capacity, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variable, energy storage battery discharging state variable, energy storage battery total power, energy storage battery capacity, grid injection power, change value of grid injection power, and total power supplied by the system to the load.

[0097] Preferably, the reservoir sharing situation includes: the micro pumped storage power stations in two substations share a downstream reservoir or the micro pumped storage power stations in two substations share an upstream reservoir.

[0098] Furthermore, when the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows:

[0099]

[0100] In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the i-th station at time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumping storage power of the i-th station at time k; is the turbine power generation at time k in the i-th station, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the i-th station, is the turbine power generation efficiency of the i-th substation, and Δt is the regulation time interval.

[0101] Furthermore, when the micro pumped storage power stations in two substations share a common upstream reservoir, the additional constraints are as follows:

[0102]

[0103] In the above formula, VH (k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the i-th station at time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

[0104] Furthermore, the first objective function is as follows:

[0105]

[0106] In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th station at time k+j, is the photovoltaic power generation power of the i-th station at time k+j, is the maximum wind power generation power at the i-th station k+j, is the wind power generation power of the i-th station at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied to the load by the system at time k+j in the i-th substation, and t is the current time.

[0107] Furthermore, the second objective function is as follows:

[0108]

[0109] In the above formula, J2 is the second objective function value, is the wind power generation capacity dispatched by the system at time k+j in the i-th area, is the photovoltaic power generation power dispatched by the system at time k+j in the i-th station, is the total pumped storage power dispatched by the system at time k+j in the i-th station, is the total pumped storage power of the i-th station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the i-th station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th area, is the energy storage battery energy of the i-th station at time k+j, is the grid injection power dispatched by the system at time k+j in the i-th substation, is the change value of the grid injection power dispatched by the system at time k+j in the i-th substation, is the change in power injected into the grid at time k+j in the ith substation, The total power of the system supply load at the i-th substation at time k+j is dispatched by the system the day before.

[0110] Furthermore, the mathematical model of the constraint condition is as follows:

[0111]

[0112] In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power at the i-th station at time k, is the maximum photovoltaic power generation power at the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the i-th substation at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the i-th substation at time k in the history day, is the maximum water storage capacity of the upstream reservoir of the ith station in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith substation in the historical day, is the energy state of the energy storage battery in the i-th station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the i-th station, is the maximum energy of the energy storage battery in the i-th station, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power generated by the reservoir at time k in the i-th station, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change in power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

[0113] Furthermore, the or 1, or 1 and when When the pumped storage unit at time k in the i-th station stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the or 1, or 1, when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

[0114] Example 3

[0115] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a real-time scheduling method for a distribution area based on a micro pumped storage power station in the above embodiment.

[0116] Example 4

[0117] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of a real-time scheduling method for a distribution area based on a micro pumped storage power station in the above embodiment.

[0118] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0119] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0120] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0121] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0122] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A real-time dispatching method for distribution area based on micro pumped storage power station, characterized in that: The method comprises: Determine additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and add the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation; Solve the real-time dispatch model of the distribution network area corresponding to the area to obtain the optimization result; Using the optimization result as a real-time dispatching plan for the substation; Among them, the real-time dispatching model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching and its corresponding constraints.

2. The method according to claim 1, characterized in that The optimization results include: photovoltaic power generation, wind power generation, water pump pumped storage power, turbine power generation, water pump working state variable, turbine working state variable, total pumped storage power, upstream reservoir water storage, downstream reservoir water storage, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variable, energy storage battery discharging state variable, energy storage battery total power, energy storage battery capacity, grid injection power, change value of grid injection power, and total power supplied by the system to the load.

3. The method according to claim 1, characterized in that The reservoir sharing situation includes: the micro pumped storage power stations in two substations share a downstream reservoir or the micro pumped storage power stations in two substations share an upstream reservoir.

4. The method according to claim 3, characterized in that When the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows: In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the ith station at the time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumped storage power of the i-th station at time k; is the power generated by the turbine at the i-th station at time k, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the ith station, is the power generation efficiency of the turbine in the ith substation, and Δt is the regulation time interval.

5. The method according to claim 4, characterized in that When the micro pumped storage power stations in two areas share an upstream reservoir, the additional constraints are as follows: In the above formula, V H (k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the ith station at the time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

6. The method according to claim 5, characterized in that The first objective function is as follows: In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th area at time k+j, is the photovoltaic power generation power of the i-th area at time k+j, is the maximum wind power generation capacity of the ith station at time k+j, is the wind power generation power of the ith area at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied by the system to the load of the ith substation at time k+j, and t is the current time.

7. The method according to claim 6, characterized in that The second objective function is as follows: In the above formula, J2 is the value of the second objective function, is the wind power generation capacity dispatched by the system at the i-th station k+j at time day ahead, is the photovoltaic power generation power dispatched by the system at the i-th station k+j time, is the total pumped storage power dispatched by the system at the i-th station k+j time, is the total pumped storage power of the ith station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the ith station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the ith station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area a day ago, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th substation, is the energy storage battery energy of the i-th station at time k+j, The power injected into the grid by the system at the i-th substation at time k+j, is the change value of the power injected into the grid by the system at the i-th substation k+j at the day before, is the change value of the power injected into the grid at the i-th substation at time k+j, It is the total power supplied by the system to the load at the i-th substation at time k+j by the system scheduled the day before.

8. The method according to claim 7, characterized in that The mathematical model of the constraint condition is as follows: In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power in the i-th area at time k, is the maximum photovoltaic power generation power of the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the ith station at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the ith substation at time k in the historical day, is the maximum water storage capacity of the upstream reservoir of the ith area in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith station in the historical day, is the energy state of the energy storage battery in the ith station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the ith area, is the maximum energy of the energy storage battery in the ith area, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power of the reservoir energy storage power generation in the i-th station area at time k, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change value of the power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

9. The method according to claim 8, characterized in that Said and when When the pumped storage unit in the i-th station at time k stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

10. A real-time dispatching device for a distribution area based on a micro pumped storage power station, characterized in that: The device comprises: The first analysis module is used to determine additional constraints based on the reservoir sharing situation of the micro pumped storage power station in the substation, and add the additional constraints to the real-time dispatch model of the distribution network substation corresponding to the substation; The second analysis module is used to solve the real-time dispatching model of the distribution network area corresponding to the area to obtain the optimization result; A scheduling module, used to use the optimization result as a real-time scheduling plan for the substation; Among them, the real-time dispatching model of the distribution network substation corresponding to the substation includes: a first objective function with the goal of abandoning wind power, photovoltaic power generation and minimizing load shedding, a second objective function with the goal of maximizing the fit between intraday dispatching and day-ahead dispatching and its corresponding constraints.

11. The device according to claim 10, characterized in that The optimization results include: photovoltaic power generation, wind power generation, water pump pumped storage power, turbine power generation, water pump working state variable, turbine working state variable, total pumped storage power, upstream reservoir water storage, downstream reservoir water storage, energy storage battery charging power, energy storage battery discharging power, energy storage battery charging state variable, energy storage battery discharging state variable, energy storage battery total power, energy storage battery capacity, grid injection power, change value of grid injection power, and total power supplied by the system to the load.

12. The device according to claim 10, characterized in that The reservoir sharing situation includes: the micro pumped storage power stations in two substations share a downstream reservoir or the micro pumped storage power stations in two substations share an upstream reservoir.

13. The device according to claim 12, characterized in that When the micro pumped storage power stations in two substations share a downstream reservoir, the additional constraints are as follows: In the above formula, V L (k+1) is the water volume of the downstream reservoir at time (k+1), V L (k) is the water volume of the downstream reservoir at time k, is the water volume of the upstream reservoir of the ith station at the time (k+1), is the water volume of the upstream reservoir of the i-th station at time k, is the pumped storage power of the i-th station at time k; is the power generated by the turbine at the i-th station at time k, ρ is the density of water, g is the acceleration of gravity, h (i) is the water head of the ith station, is the water pump energy storage efficiency of the ith station, is the power generation efficiency of the turbine in the ith substation, and Δt is the regulation time interval.

14. The device according to claim 13, characterized in that When the micro pumped storage power stations in two areas share an upstream reservoir, the additional constraints are as follows: In the above formula, V H (k+1) is the water volume of the upstream reservoir at time (k+1), V H (k) is the water volume of the upstream reservoir at time k, is the water volume of the downstream reservoir of the ith station at the time (k+1), is the water volume of the downstream reservoir of the i-th substation at time k.

15. The device according to claim 14, characterized in that The first objective function is as follows: In the above formula, J1 is the first objective function value, N is the prediction end time, ε is the first coefficient, σ is the second coefficient, φ is the third coefficient, is the maximum photovoltaic power generation power of the i-th area at time k+j, is the photovoltaic power generation power of the i-th area at time k+j, is the maximum wind power generation capacity of the ith station at time k+j, is the wind power generation power of the ith area at time k+j, Inject grid power into the i-th substation at time k+j, is the line load power, is the total power supplied by the system to the load of the ith substation at time k+j, and t is the current time.

16. The device according to claim 15, characterized in that The second objective function is as follows: In the above formula, J2 is the value of the second objective function, is the wind power generation capacity dispatched by the system at the i-th station k+j at time day ahead, is the photovoltaic power generation power dispatched by the system at the i-th station k+j time, is the total pumped storage power dispatched by the system at the i-th station k+j time, is the total pumped storage power of the ith station at time k+j, is the upper reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the ith station at time k+j, is the lower reservoir capacity of the system scheduled at time k+j in the i-th substation, is the reservoir capacity of the ith station at time k+j, is the total power of the energy storage battery dispatched by the system at time k+j in the i-th area a day ago, is the total power of the energy storage battery in the i-th station at time k+j, is the energy storage battery energy dispatched by the system at time k+j in the i-th substation, is the energy storage battery energy of the i-th station at time k+j, The power injected into the grid by the system at the i-th substation at time k+j, is the change value of the power injected into the grid by the system at the i-th substation k+j at the day before, is the change value of the power injected into the grid at the i-th substation at time k+j, It is the total power supplied by the system to the load at the i-th substation at time k+j by the system scheduled the day before.

17. The device according to claim 16, characterized in that The mathematical model of the constraint condition is as follows: In the above formula, is the photovoltaic power generation power of the i-th station at time k, is the wind power generation power in the i-th area at time k, is the maximum photovoltaic power generation power of the i-th station at time k, is the maximum wind power generation power at the i-th station at time k, is the energy storage power of the water pump in the i-th station at time k, is the maximum energy storage power of the water pump in the ith station at time k in the historical day, is the power generation of the turbine in the i-th station at time k, is the maximum power generation of the turbine in the ith substation at time k in the historical day, is the maximum water storage capacity of the upstream reservoir of the ith area in the historical day, is the maximum water storage capacity of the downstream reservoir of the ith station in the historical day, is the energy state of the energy storage battery in the ith station at time k+1, is the energy state of the energy storage battery in the i-th station at time k, is the charging efficiency of the energy storage battery, is the charging power of the energy storage battery, is the discharge power of the energy storage battery, is the discharge efficiency of the energy storage battery, Δt is the control time interval, DOD (i) is the discharge depth of the energy storage battery in the ith area, is the maximum energy of the energy storage battery in the ith area, is the maximum charging power of the energy storage battery, is the maximum discharge power of the energy storage battery, The grid power injected into the i-th substation at time k is: is the total power of the reservoir energy storage power generation in the i-th station area at time k, is the total charging and discharging power of the energy storage battery in the i-th station at time k, is the power consumed by the line load at the i-th station at time k, is the working state variable of the pumped storage unit, is the working state variable of the turbine generator set, is the charging state variable of the energy storage battery at time k, is the discharge state variable of the energy storage battery at time k, is the change value of the power injected into the transmission network of the ith substation at time k, and δ is the impact threshold.

18. The device according to claim 17, characterized in that Said and when When the pumped storage unit in the i-th station at time k stops running, When the pumped storage unit at time k in the i-th station starts to operate, When the turbine generator set at time k in the i-th station stops running, When the turbine generator set at time k in the i-th station starts running, the when When the energy storage battery stops charging, The energy storage battery starts charging when When the energy storage battery stops discharging, The energy storage battery starts to discharge.

19. A computer device, characterized in that: include: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the real-time scheduling method for distribution station area based on micro pumped storage power station as described in any one of claims 1 to 9 is implemented.

20. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the real-time dispatching method for distribution station area based on micro pumped storage power station as described in any one of claims 1 to 9 is implemented.

Images