Power grid dispatching method and device, power equipment, readable storage medium and program product

Abstract

The invention relates to a power grid dispatching method and device, power equipment, a computer readable storage medium and a computer program product. The method comprises the steps of determining storage capacity according to power generation information of a power grid; based on the electricity storage quantity, constructing a power supply quantity control virtual queue; constructing an indoor temperature virtual queue; determining the delay time required for waiting for the current electricity price to be lower than the preset electricity price and the charging amount required by the electric vehicle, constructing an electric quantity queue, and constructing a delay virtual queue; constraining an electric quantity queue according to the delay time and the delay virtual queue; constructing a Lyapunov function according to the power supply quantity control virtual queue, the indoor temperature virtual queue, the electric quantity queue and the delay virtual queue; and according to the expected value of the Lyapunov function based on the time change, drift and penalty terms are determined to perform power grid dispatching, so that the power consumption demand is met and the power consumption cost is reduced. According to the method, the power consumption demand can be ensured while the power consumption cost is reduced based on power grid dispatching, so that the accuracy of power grid dispatching is improved.

Description

Technical Field

[0001] The present application relates to the field of electric power technology, and in particular to a power grid dispatching method, apparatus, electric power equipment, computer-readable storage medium, and computer program product. Background Art

[0002] Grid dispatching refers to the process of managing and controlling the power generation, transmission and distribution of the power system. As the diversification and complexity of power generation and consumption have put forward higher requirements for grid dispatching, how to improve the accuracy of grid dispatching is a problem that needs to be solved. Summary of the invention

[0003] Based on this, it is necessary to provide a power grid dispatching method, device, power equipment, computer-readable storage medium and computer program product to address the above technical problems.

[0004] In a first aspect, the present application provides a power grid dispatching method, comprising:

[0005] Determine the power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; determine the power storage capacity of the power grid based on the power generation information; and build a virtual queue for power supply control based on the power storage capacity;

[0006] Determine the air conditioning power usage information required to keep the indoor temperature within the target temperature range; and construct an indoor temperature virtual queue based on the air conditioning power usage information;

[0007] Based on the change of electricity price over time, determine the delay time required to wait for the current electricity price to be lower than the preset electricity price, and the charging amount required for the electric vehicle corresponding to the delay time; and construct an electric power queue corresponding to the charging of the electric vehicle according to the charging amount; construct a delayed virtual queue corresponding to the electric power queue, and constrain the electric power queue according to the delay time and the delayed virtual queue;

[0008] According to the power supply control virtual queue, indoor temperature virtual queue, power queue and delay virtual queue, a Lyapunov function is constructed;

[0009] Determine the expected value of a Lyapunov function over time;

[0010] According to the expected value, determine the drift and penalty terms;

[0011] Based on the drift plus penalty term, the power grid is dispatched to meet the electricity demand and reduce the electricity cost.

[0012] In one embodiment, the aforementioned power grid dispatching method further includes:

[0013] Determine the start and stop time of the air conditioner according to the distribution of indoor personnel;

[0014] Based on the change of air conditioner start and stop time and electricity price over time, a total estimated cost function is constructed;

[0015] Based on the expected value, determine the drift and penalty terms, including:

[0016] Based on the expected value and the total estimated cost function, the drift and penalty terms are determined.

[0017] In one embodiment, a Lyapunov function is constructed according to a power supply control virtual queue, an indoor temperature virtual queue, a power queue, and a delay virtual queue, including:

[0018]

[0019] Among them, H t is the indoor temperature virtual queue; Q t It is the power queue;

[0020] Z t is the delayed virtual queue; K t Provides a virtual queue for power control.

[0021] In one embodiment, the air conditioner power usage information includes the air conditioner input power; and constructing the indoor temperature virtual queue according to the air conditioner power usage information includes:

[0022] The indoor temperature under air conditioning is dynamically calculated based on the following formula:

[0023]

[0024] Among them, T t is the indoor temperature at time t; T t+1 is the indoor temperature at time t+1; is the outdoor temperature at time t; η is the thermal efficiency; A is the thermal conductivity; ω is the time constant; ε = e -τ / ω ;e t is the air conditioning input power at time t;

[0025] Based on the first calculation formula and the second calculation formula, a virtual indoor temperature queue H is constructed. t ; Indoor temperature virtual queue H t Corresponding to the change of indoor temperature:

[0026] The first calculation formula is: H t =T t +Γ, where Γ is a constant term;

[0027] The second calculation formula is H t Dynamic calculation formula:

[0028] Among them, Tout is the outdoor temperature.

[0029] In one embodiment, according to the charging amount, a power queue corresponding to the charging of the electric vehicle is constructed, including:

[0030] According to the following calculation formula, the power queue Q corresponding to the electric vehicle charging is constructed t :

[0031] Q t+1 =max[Q t -x t ,0]+a t ;

[0032] Among them, x t and a t are the service rate and arrival rate of the power queue respectively; x max For x t The highest value, x max ≥a max , so that the queue remains stable; 0≤x t ≤min{x max , Q t}, so that x t Not greater than the power queue Q t of charge.

[0033] In one embodiment, constructing a delayed virtual queue corresponding to the power queue, and constraining the power queue according to the delay time and the delayed virtual queue, includes:

[0034] The delayed virtual queue is constructed based on the following formula:

[0035]

[0036] Among them, Z t is the delayed virtual queue with time t; Z t+1 is the delayed virtual queue at time t+1; ξ is a fixed parameter representing Q t >x t Virtual queue Z t The arrival rate of x t For queue Z t service rate;

[0037] Constrain the power queue according to the following formula:

[0038] D max ≤R;

[0039] Where R represents the delay time; D max Indicates the maximum queue delay of the power queue, Z maxIndicates the maximum value corresponding to the delayed virtual queue.

[0040] In a second aspect, the present application further provides a power grid dispatching device, the device comprising:

[0041] A queue construction module is used to determine the power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; according to the power generation information, determine the power storage capacity of the power grid; and based on the power storage capacity, construct a power supply control virtual queue; determine the air conditioning power consumption information required to make the indoor temperature within the target temperature range; and construct an indoor temperature virtual queue based on the air conditioning power consumption information; based on the change of electricity price over time, determine the delay time required to wait for the current electricity price to be lower than the preset electricity price, and the charging amount required for the electric vehicle corresponding to the delay time; and construct a power queue corresponding to the charging of the electric vehicle based on the charging amount; and construct a delay virtual queue based on the delay time to constrain the power queue;

[0042] A determination module is used to control a virtual queue, an indoor temperature virtual queue, a power queue and a delay virtual queue according to the power supply amount, and construct a Lyapunov function; determine an expected value of the Lyapunov function based on time changes; and determine a drift and a penalty term according to the expected value;

[0043] The scheduling module is used to schedule the power grid according to the drift plus penalty item to meet the power demand and reduce the power cost.

[0044] In a third aspect, the present application further provides an electric power device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the first aspect when executing the computer program.

[0045] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method in the first aspect when executed by a processor.

[0046] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements the steps of the method in the first aspect when executed by a processor.

[0047] The above-mentioned power grid dispatching method, device, power equipment, computer-readable storage medium and computer program product, by constructing a power supply control virtual queue, an indoor temperature virtual queue, a power queue and a delay virtual queue, which cover the power generation side and the power consumption side of the power grid, ensure the accuracy of power grid dispatching; construct a Lyapunov function through the above-mentioned queues, so as to determine the corresponding drift and penalty items. Since the above-mentioned queues involve the power storage capacity of the power grid, the power consumption of air conditioners, the charging capacity and delay time required for electric vehicles, etc., the power grid is dispatched according to the drift and penalty items, which can reduce the electricity cost based on the power grid dispatching while ensuring the electricity demand, thereby improving the accuracy of the power grid dispatching; at the same time, the power grid dispatching based on Lyapunov function, drift and penalty items, etc., helps to ensure the stability of the power grid and improve the efficiency of the power grid dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 A schematic diagram of a flow chart of a power grid dispatching method in one embodiment;

[0050] Figure 2 is another schematic flow chart of a power grid dispatching method in one embodiment;

[0051] Figure 3 1 is another flow chart of a power grid dispatching method in one embodiment;

[0052] Figure 4 is a structural block diagram of a power grid dispatching device in one embodiment;

[0053] Figure 5 FIG. 4 is a diagram showing the internal structure of an electric power device in one embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] The following is an explanation of the technical terms related to the technical solution of this application:

[0056] Lyapunov function is a function that can describe the stability of a dynamic system. The basic idea is that if an appropriate Lyapunov function V(x) can be found so that V(x) decreases monotonically with time as the system state x changes, then the system is asymptotically stable.

[0057] Drift-Plus-Penalty is an algorithm for analyzing and optimizing stochastic systems. This method is particularly suitable for systems with time-varying or uncertainties, such as communication networks, queuing systems, inventory control, etc. This method combines the concepts of Lyapunov stability theory and achieves stability and performance optimization by minimizing an objective function that includes "drift" and "penalty".

[0058] Consumption: refers to the transmission of electricity generated by power plants to users so that they can be effectively utilized.

[0059] Arrival rate: A basic concept in queuing theory, which refers to the average number of customers or tasks that arrive at the system per unit time. The arrival rate can be used to measure the frequency with which the system is requested for service. For example, if 5 new tasks arrive at the server every minute, the arrival rate is 5 tasks / minute. "System" corresponds to the specific queue in this application.

[0060] Service rate: A basic concept in queuing theory, which refers to the number of services that a system can complete per unit time. The service rate reflects the system's ability to handle tasks. For example, if a service desk can handle one task every 20 seconds on average, then its service rate is 3 tasks / minute. "System" corresponds to the specific queue in this application.

[0061] After the above-mentioned nouns are explained, the technical solution provided by this application is described below:

[0062] With the diversification of power generation methods, wind power generation, solar power generation and other methods have emerged, but these power generation methods have uncertainties, such as changes in wind speed and solar radiation. Through grid dispatching, the safe and stable operation of the grid, reliable external power supply, and orderly progress of various types of power production are guaranteed. With the rapid development of renewable energy, higher requirements are placed on grid dispatching. In the existing technology, most of the grid dispatching that takes into account the consumption of new energy focuses on reducing electricity costs, but ignores electricity demand, that is, no reasonable online dispatching is carried out in combination with electricity demand, which leads to poor accuracy of grid dispatching.

[0063] Based on the above analysis, this application provides a power grid dispatching method, which takes into account new energy power generation such as wind power generation and solar power generation, takes air conditioning power consumption and new energy vehicle charging as two major categories of power consumption, constructs multiple virtual queues for power consumption, and constructs a Lyapunov function based on multiple virtual queues to determine the drift plus penalty term, and performs power grid dispatching based on the drift plus penalty term to meet power demand and reduce power costs. The following is further explained by way of embodiments:

[0064] In one embodiment, a power grid dispatching method is provided. This embodiment illustrates the method by applying it to a power system. It is understandable that the method can also be applied to special power grid dispatching equipment, systems, and platforms.

[0065] like Figure 1 As shown, in this embodiment, the method includes steps S102 to S108:

[0066] Step S102: Determine the power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; determine the power storage capacity of the power grid according to the power generation information; and construct a power supply control virtual queue based on the power storage capacity.

[0067] The power generation information may include information corresponding to photovoltaic power generation and information corresponding to wind power generation in the power grid, for example, power generation capacity.

[0068] The power supply control virtual queue may be a virtual queue related to power supply control of a power grid, which is used to serve the construction of a subsequent Lyapunov function.

[0069] In some embodiments, the power generation information may be obtained based on real-time detection and / or real-time calculation. For example, the power generation status of the corresponding power generation equipment is calculated according to the real-time wind speed, thereby obtaining the wind power generation information.

[0070] In some embodiments, the power storage capacity of the power grid determined based on the power generation information may be greater than or equal to the power range required to be consumed by the power consumption equipment corresponding to the power grid.

[0071] For the consumption of electric energy, we can mainly consider the two aspects of air conditioning power consumption and electric vehicle charging, and build corresponding virtual queues. The details are as follows:

[0072] Step S104: determining the air-conditioning power usage information required to make the indoor temperature within the target temperature range; and constructing an indoor temperature virtual queue according to the air-conditioning power usage information.

[0073] Step S106: Based on the change of electricity price over time, determine the delay time required to wait for the current electricity price to be lower than the preset electricity price, and the charging amount required for the electric vehicle corresponding to the delay time; and construct an electricity queue corresponding to the charging of the electric vehicle according to the charging amount; construct a delayed virtual queue corresponding to the electricity queue, and constrain the electricity queue according to the delay time and the delayed virtual queue.

[0074] Among them, electric vehicle charging can be understood in a broad sense, including but not limited to electric bus charging, electric taxi charging, electric truck charging and electric private car charging, etc. Electric vehicles can be understood in a broad sense, including but not limited to pure electric vehicles, hybrid vehicles, and battery vehicles, etc.

[0075] In some embodiments, the price of electricity can change over time, such as the price of electricity at 1 a.m. is lower than the price at 12 a.m., so the charging time of the electric vehicle can be adjusted to reduce the corresponding electricity cost. In this regard, two aspects need to be considered: one is the required charging amount, according to which a corresponding power queue can be constructed; the other is the delay time, that is, the time required to wait for the electricity price to drop to the preset price, and a corresponding delay virtual queue can be constructed. The delay virtual queue is for electric vehicle charging, and can be used to constrain the power queue and limit the time required to complete the corresponding charging amount, so as to avoid insufficient charging, excessive charging time, etc.

[0076] In some embodiments, the maximum queuing delay required for charging corresponding to the power queue can be determined based on the delayed virtual queue, and the power queue can be constrained by ensuring that the maximum queuing delay is less than or equal to the delay time.

[0077] Step S108: construct a Lyapunov function according to the power supply control virtual queue, indoor temperature virtual queue, power queue and delay virtual queue; determine the expected value of the Lyapunov function based on time change; determine the drift and penalty items according to the expected value; and perform grid scheduling based on the drift plus the penalty item to meet electricity demand and reduce electricity costs.

[0078] In some embodiments, the above steps construct a power supply control virtual queue, an indoor temperature virtual queue, a power queue and a delay virtual queue, which cover the power generation side and the power consumption side of the power grid. Based on the above queues, the corresponding Lyapunov function can be constructed, and the expected value of the Lyapunov function based on time changes can be determined. According to the expected value, the drift and penalty terms are determined to perform power grid scheduling, thereby meeting power demand and reducing power costs.

[0079] In some embodiments, the expected value of the change at the next time compared to the current time can be calculated as the drift and penalty amount. When the drift plus penalty term is adopted, the real-time scheduling optimization is performed by continuously optimizing and adjusting the scheduling scheme. The long-term goal optimization is achieved by minimizing the drift plus penalty term while maintaining system stability.

[0080] In the above-mentioned power grid dispatching method, a power supply control virtual queue, an indoor temperature virtual queue, a power queue and a delay virtual queue are constructed, which cover the power generation side and the power consumption side of the power grid to ensure the accuracy of power grid dispatching; a Lyapunov function is constructed through the above-mentioned queues to determine the corresponding drift and penalty items. Since the above-mentioned queues involve the power storage capacity of the power grid, the power consumption of air conditioners, the charging amount and delay time required for electric vehicles, etc., the power grid dispatching is carried out according to the drift and penalty items, which can reduce the electricity cost based on the power grid dispatching while ensuring the electricity demand, thereby improving the accuracy of the power grid dispatching; at the same time, the power grid dispatching based on Lyapunov function, drift and penalty items, etc., helps to ensure the stability of the power grid and improve the efficiency of the power grid dispatching.

[0081] In one embodiment, if Figure 2 As shown, the aforementioned power grid dispatching method may further include steps S202 to S206:

[0082] Step S202: Determine the start and stop time of the air conditioner according to the distribution of people in the room.

[0083] For example, when the indoor occupant distribution situation indicates that there is no one in the room, the air conditioner stops running, otherwise, the air conditioner starts running.

[0084] In some embodiments, the air conditioners are independent of each other and can be started and stopped individually according to the distribution of people in the room.

[0085] Step S204: construct a total estimated cost function based on the air conditioner start and stop times and the change in electricity prices over time.

[0086] For example, the total estimated cost function may be VE{Φ 1，t +Φ 2，t |Ψ t}, where V is the weight parameter for balancing the queue stability; Φ 1，t represents the electricity price; Φ 2，t It indicates that the air conditioner is not suitable to be turned on during time period t. It is added to the electricity price to minimize the total energy and the cost of not being suitable to turn on the air conditioner.

[0087] The aforementioned “determining drift and penalty items according to the expected value” may include step S206: determining drift and penalty items according to the expected value and the total estimated cost function.

[0088] By taking into account the changes in air conditioner start and stop times and electricity prices over time, a total estimated cost function is constructed, and this function is used to determine drift and penalty terms. As a result, subsequent grid scheduling based on drift and penalty terms can more accurately reduce electricity costs while ensuring electricity demand.

[0089] In one embodiment, the aforementioned “constructing a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue” may include:

[0090] Among them, H t is the indoor temperature virtual queue; Q t is the power queue; Z t is the delayed virtual queue; K t Provides a virtual queue for power control.

[0091] In one embodiment, the aforementioned “air conditioner power consumption information includes air conditioner input power; and building an indoor temperature virtual queue according to the air conditioner power consumption information” may include: dynamically calculating the indoor temperature under the action of the air conditioner based on the following formula:

[0092] Among them, T t is the indoor temperature at time t; T t+1 is the indoor temperature at time t+1; is the outdoor temperature at time t; η is the thermal efficiency; A is the thermal conductivity; ω is the time constant; ε = e -τ / ω ;e t is the air conditioning input power at time t;

[0093] Based on the first calculation formula and the second calculation formula, a virtual indoor temperature queue H is constructed. t ; Indoor temperature virtual queue H t Corresponding to the change of indoor temperature:

[0094] The first calculation formula is: H t =T t +Γ, where Γ is a constant term;

[0095] The second calculation formula is H t Dynamic calculation formula:

[0096] Among them, T out is the outdoor temperature.

[0097] Since the indoor temperature may be changing rather than being maintained stably, the indoor temperature is determined dynamically through the above formula, which can more accurately determine the indoor temperature under the action of air conditioning, thereby constructing a more accurate indoor temperature virtual queue, providing a more accurate basis for the determination of subsequent drift and penalty items.

[0098] In one embodiment, the aforementioned “building a power queue corresponding to the charging of the electric vehicle according to the charging amount” may include: building a power queue Q corresponding to the charging of the electric vehicle according to the following calculation formula:t :

[0099] Q t+1 =max[Q t -x t ,0]+a t ;

[0100] Among them, x t and a t are the service rate and arrival rate of the power queue respectively; x max For x t The highest value, x max ≥a max , so that the queue remains stable; 0≤x t ≤min{x max , Q t}, so that x t Not greater than the power queue Q t of charge.

[0101] In some embodiments, x t and a t They are the service and arrival process of the energy queue. The Lyapunov function can transform the long-term optimization problem into multiple online sub-problems through queue stability management, so the energy queue Q is established. t , which helps in online EV charging scheduling and enables EV charging to be postponed when electricity prices are high.

[0102] Through the above method, for electric vehicle charging, from the perspective of queuing theory, the service rate and arrival rate of the power queue are considered, which helps to build a more accurate power queue.

[0103] In one embodiment, the aforementioned “constructing a delayed virtual queue corresponding to the power queue, and constraining the power queue according to the delay time and the delayed virtual queue” may include: constructing the delayed virtual queue based on the following formula:

[0104] Among them, Z t is the delayed virtual queue with time t; Z t+1 is the delayed virtual queue at time t+1; ξ is a fixed parameter representing Q t >x t Virtual queue Z t The arrival rate of x t For queue Z t service rate;

[0105] Constrain the power queue according to the following formula: D max ≤R; R represents the delay time; D max Indicates the maximum queue delay of the power queue, Z max Indicates the maximum value corresponding to the delayed virtual queue. Exemplarily, the maximum queuing delay of the power queue can be determined and / or constrained by delaying the maximum value corresponding to the virtual queue, and the maximum queuing delay is constrained by the delay time, thereby constraining the power queue.

[0106] Through the above method, for electric vehicle charging, taking into account the fluctuation of electricity prices over time, there is a corresponding delay time to reduce the corresponding electricity cost. By constructing a delayed virtual queue corresponding to the power queue, the virtual queue and delay time are used to constrain the power queue. This helps to build a more accurate power queue and avoid excessive maximum queue delay and affect electricity demand.

[0107] In one embodiment, in order to conduct reasonable online scheduling in combination with electricity demand, a power grid scheduling method is provided. This method can reduce electricity costs while taking into account electricity demand such as air conditioning and new energy vehicle charging, and can cover different electricity usage scenarios and conduct real-time online scheduling. Please refer to Figure 3 , Figure 3 A possible process flow diagram of a power grid dispatching method is provided, and the method may include steps S302 to S306:

[0108] Step S302: construct a new energy power generation model, which includes a photovoltaic model and a wind energy model.

[0109] The output power of the photovoltaic model t The calculation formula is:

[0110]

[0111] in, Represents the energy efficiency of photovoltaics, A pu represents the photovoltaic area, Temp(t) represents the solar radiation temperature, I rr (t) represents the outdoor temperature; 0.005 is a constant representing the temperature correction coefficient.

[0112] Wind energy model: Output power pwt of wind energy model t The calculation formula is: Let v r Indicates wind cut-in speed = 4m / s; v indicates wind rated speed 12m / s; v co Indicates wind cut-off wind speed = 25m / s:

[0113] If ν ≥ ν r &&ν≤ν co , we can get:

[0114] pwt t =k 2 P r (2).

[0115] Step S304: constructing a consumption model, which includes: an air conditioning model and an electric vehicle charging model.

[0116] The consumption scenarios can be divided into two typical application scenarios: one is high-power electrical equipment, such as air conditioners; the other is high-power charging equipment, such as electric vehicle charging piles.

[0117] The process of building the air conditioning model is as follows: Let e t is the real-time power consumption of the air conditioner. The power demand calculation formula of the air conditioner is:

[0118] 0≤e t ≤e max (3)

[0119] Among them, e max Indicates the maximum load of the air conditioner, e t represents the air conditioning power demand at time t;

[0120] The dynamic calculation formula for indoor temperature in air-conditioning environment is:

[0121]

[0122] Among them, T t and denote indoor and outdoor temperatures respectively, η denotes thermal efficiency, A denotes thermal conductivity, ω denotes time constant, ε = e-τ / ω;

[0123] Add constraints to formula (4) to ensure that the indoor temperature changes within a comfortable temperature range:

[0124] T min ≤T t ≤T max (5);

[0125] Among them, T min and T max Represent the lowest and highest temperatures in the range respectively.

[0126] The process of building an electric vehicle charging model is as follows: the electric vehicle charging model is used to schedule electric vehicles to charge when electricity prices are low and postpone charging when electricity prices are high; in order to complete charging within the specified time, the long-term optimization problem is converted into multiple online sub-problems through queue stability management based on the Lyapuno function.

[0127] In some embodiments, efficient charging of electric vehicles (EVs) is ensured by optimizing charging time and location. When a fleet or a public charging station performs EV charging scheduling, the EV charging location and charging time can be arranged by calculating the power queue.

[0128] A possible specific implementation is provided below:

[0129] Establishing the energy queue Q t (That is, the aforementioned power queue):

[0130] Q t+1 =max[Q t -x t ,0]+a t (6)

[0131] Among them, x t and a t are the service rate and arrival rate of the power queue respectively. For example, x t and a t They are the service and arrival process of the energy queue respectively. The Lyapuno function can transform the long-term optimization problem into multiple online sub-problems through queue stability management, thus establishing the energy queue Q t , which facilitates online EV charging scheduling to defer EV charging when electricity prices are high.

[0132] Let x max For x t The highest value of x max ≥a max Make the queue Q t Keep stable, but not greater than Q t Power demand:

[0133] 0≤x t ≤min{x max , Q t} (7),

[0134] In some embodiments, when an electric vehicle is connected for charging, a triplet request is provided, which includes the expected charging time s, the expected charging completion time c, and the total energy E required for full charging. In order to cope with the time variation of dynamic pricing, the power demand of electric vehicles should be met so that electric vehicles can be charged when the electricity price is low and the charging of electric vehicles can be postponed when the electricity price is high. In order to achieve this criterion without exceeding the completion time, the power queue Q t And constrain the length of the power queue. The following is a possible specific implementation method:

[0135] Add constraints so that Q t The average length of is finite:

[0136]

[0137] Formula (8) is constrained by formula (9) to ensure that the expected charging completion time is not exceeded:

[0138] D max ≤R (9),

[0139] Among them, D max Represents queue Q t The maximum queuing delay, R, represents the acceptable delay charging time.

[0140] Step S306: construct a virtual queue related to the electric vehicle charging delay and the indoor temperature of the air conditioner, and obtain a drift plus penalty item to implement a method for optimizing the real-time scheduling of the power grid.

[0141] Let G t Represents the power supply of the grid energy storage system, G t =r t +pwt t ; Add constraints to ensure that the total power used by all consumption equipment is less than the maximum power supply of the grid energy storage system:

[0142] G min ≤G t ≤G max (10)

[0143] Among them, G max and G min Respectively represent the maximum and minimum power supply of the grid energy storage system. This is the added constraint condition, which ensures that the total power used by all consumption equipment is less than the maximum power supply of the grid energy storage system on the one hand, and ensures that the power supply of the grid energy storage system cannot be lower than the minimum power supply on the other hand.

[0144] By constructing electric vehicle charging delay and delay-aware virtual queues, the electric vehicle charging power and air conditioning power consumption can be reasonably arranged. The corresponding process of constructing a virtual queue is:

[0145] First, the virtual queue H t (i.e. the aforementioned indoor temperature virtual queue) is the variation of indoor temperature, which is defined as follows:

[0146] H t =T t +Γ (11), where T t Indicates the indoor temperature;

[0147] H t The dynamic calculation formula is:

[0148]

[0149] Among them, T out Indicates outdoor temperature; e t Indicates the air conditioner input power.

[0150] Second, to satisfy formula (9), let Z t is the delay-aware virtual queue (i.e. the aforementioned delay virtual queue), and the calculation formula is:

[0151]

[0152] Among them, ξ is a fixed parameter, representing Q t >x t Virtual queue Z t The arrival rate, x t For queue Z t The service rate of queue Z t and Q t If there is an upper limit, then formula (9) can be satisfied;

[0153] The maximum queue calculation formula is:

[0154] In order to ensure the feasibility of formula (10), a virtual queue (i.e., the aforementioned power supply control virtual queue) is defined in formula (14):

[0155] K t =G t +α, (14), where α is a constant;

[0156] K t The dynamic calculation formula is:

[0157] K t+1 =K t +α, (15).

[0158] The process of obtaining the drift plus penalty term is:

[0159] Power Queue Q t Formula (8) should be satisfied, therefore, the Lyapunov function is defined as follows:

[0160]

[0161] Among them, H t is the indoor temperature virtual queue; Q t is the electric vehicle power queue; Z t Delayed virtual queues for electric vehicle charging; K t Control virtual queues for power supply from grid energy storage systems.

[0162] Design Lyapunov function: Δ t =E{L t+1 -L t |ψ t} (17);

[0163] All assumptions are based on changes in outdoor temperature, renewable energy generation, electric vehicle charging requirements, the most comfortable temperature setting, and control decisions. From formula (16), we can see that:

[0164]

[0165] In the formula,

[0166]

[0167]

[0168] In the formula, The upper limits are:

[0169]

[0170]

[0171] In the formula,

[0172]

[0173] Among them, a t Indicates Q t Queue arrival rate;

[0174] x t Indicates Q t queue service rate;

[0175] y t Indicates the power supply power of the grid energy storage system;

[0176] T out min and T out max Respectively represent the minimum and maximum outdoor temperatures;

[0177] e max Indicates the maximum power of the air conditioner;

[0178] u c max Indicates the maximum charging power of new energy;

[0179] u d max Indicates the maximum discharge power of the grid energy storage system.

[0180] When the total expected cost function VE{Φ 1，t +Φ 2，t |Ψ t When} is added to formula (17), the drift plus penalty term is generated as follows:

[0181]

[0182] In the formula,

[0183] Among them, V is the weight parameter of the balanced queue stability;

[0184] Φ 1，t represents the price of electricity;

[0185] Φ 2，t It indicates that the air conditioner is not suitable for use during time period t, and it is added to the electricity price to minimize the total energy and the cost of not suitable for use of air conditioner; γ is the cost coefficient;

[0186] In some embodiments, the expectation in the total expected cost function may be calculated using the following method:

[0187] Where E is the expectation operator;

[0188] Represents the most comfortable temperature for residents at T+1;

[0189] Π t+1 represents the state of the house at t+1;

[0190] When t+1 =0, indicating that no one is at home, then Φ 2，t =0;

[0191] Use T t+1 |e t =0 to represent: air conditioning input power e t =0, indoor temperature T t+1 When the house is vacant or T t+1 |e t =0 greater than the comfortable temperature T min , the air conditioner cannot realize the dispatch of power supply from the power grid.

[0192] In some embodiments, the expected value of the change at the next time compared to the current time can be calculated as the drift and penalty. When the drift plus penalty term is used, the objective function contains the unknown amount of scheduling power, and real-time scheduling optimization is performed by continuously optimizing and adjusting the scheduling scheme. Long-term target optimization is achieved by minimizing the drift plus penalty term while maintaining system stability.

[0193] By constructing a power supply control virtual queue, an indoor temperature virtual queue, a power queue and a delay virtual queue, a Lyapunov function is constructed through the above queues, and a total estimated cost function is constructed by taking into account the changes in the start and stop time of the air conditioner and the electricity price over time. The drift and penalty items are determined according to the Lyapunov function and the total estimated cost function. Since the above queues involve the power storage capacity of the power grid, the power consumption of the air conditioner, the charging amount and delay time required for the electric vehicle, etc., the power grid is dispatched according to the drift and penalty items, which can reduce the electricity cost based on the power grid dispatch while ensuring the electricity demand, thereby improving the accuracy of the power grid dispatch; at the same time, the power grid dispatch based on the Lyapunov function, drift and penalty items, etc., is helpful to ensure the stability of the power grid and improve the efficiency of the power grid dispatch. At the same time, by dynamically determining the indoor temperature, the indoor temperature under the effect of air conditioning can be determined more accurately, thereby constructing a more accurate indoor temperature virtual queue; for electric vehicle charging, from the perspective of queuing theory, the service rate and arrival rate of the power queue are considered, which helps to build a more accurate power queue; taking into account that electricity prices fluctuate over time, there is a corresponding delay time to reduce the corresponding electricity cost. By constructing a delayed virtual queue corresponding to the power queue, the virtual queue and delay time are used to constrain the power queue, which helps to build a more accurate power queue and avoid excessive maximum queue delay and affect electricity demand.

[0194] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0195] Based on the same inventive concept, the embodiment of the present application also provides a power grid dispatching device for implementing the power grid dispatching method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more power grid dispatching device embodiments provided below can refer to the limitations on the power grid dispatching method above, and will not be repeated here.

[0196] In an exemplary embodiment, Figure 4 As shown, a power grid dispatching device 400 is provided, comprising:

[0197] The queue construction module 401 is used to determine the power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; determine the power storage capacity of the power grid according to the power generation information; and construct a power supply control virtual queue based on the power storage capacity; determine the air conditioning power consumption information required to make the indoor temperature within the target temperature range; and construct an indoor temperature virtual queue based on the air conditioning power consumption information; determine the delay time required to wait for the current power price to be lower than the preset power price based on the change of power price over time, and the charging amount required for the electric vehicle corresponding to the delay time; and construct a power queue corresponding to the charging of the electric vehicle according to the charging amount; construct a delay virtual queue corresponding to the power queue, and constrain the power queue according to the delay time and the delay virtual queue;

[0198] The determination module 402 is used to construct a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue; determine the expected value of the Lyapunov function based on time change; and determine the drift and penalty terms according to the expected value;

[0199] The scheduling module 403 is used to perform power grid scheduling based on drift plus penalty items to meet power demand and reduce power costs.

[0200] In one embodiment, the determination module 402 is also used to determine the start and stop time of the air conditioner according to the distribution of indoor personnel; construct a total expected cost function based on the changes in the start and stop time of the air conditioner and the electricity price over time; determine the drift and penalty items according to the expected value, including: determining the drift and penalty items according to the expected value and the total expected cost function.

[0201] In one embodiment, the determination module 402 is further used to construct a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue, including:

[0202] Among them, H t is the indoor temperature virtual queue; Q t is the power queue; Z t is the delayed virtual queue; K t Provides a virtual queue for power control.

[0203] In one embodiment, the air conditioner power consumption information includes the air conditioner input power; the queue construction module 401 is further used to construct an indoor temperature virtual queue according to the air conditioner power consumption information, including: dynamically calculating the indoor temperature under the action of the air conditioner based on the following formula:

[0204] Among them, T t is the indoor temperature at time t; T t+1 is the indoor temperature at time t+1; is the outdoor temperature at time t; η is the thermal efficiency; A is the thermal conductivity; ω is the time constant; ε = e -τ / ω ;e t is the air conditioning input power at time t;

[0205] Based on the first calculation formula and the second calculation formula, a virtual indoor temperature queue H is constructed. t ; Indoor temperature virtual queue H t Corresponding to the change of indoor temperature: Among them, the first calculation formula is: H t =T t +Γ, where Γ is a constant term; the second calculation formula is H t Dynamic calculation formula:

[0206] Among them, T out is the outdoor temperature.

[0207] In one embodiment, the queue construction module 401 is further used to construct a power queue corresponding to the charging of the electric vehicle according to the charging amount, including: constructing the power queue Q corresponding to the charging of the electric vehicle according to the following calculation formula t :

[0208] Q t+1 =max[Q t -x t ,0]+a t ; where x t and a t are the service rate and arrival rate of the power queue respectively; x max For x t The highest value, x max ≥a max , so that the queue remains stable; 0≤x t ≤min{x max , Q t}, so that x t Not greater than the power queue Q t of charge.

[0209] In one embodiment, the queue construction module 401 is further used to construct a delayed virtual queue corresponding to the power queue, and constrain the power queue according to the delay time and the delayed virtual queue, including:

[0210] The delayed virtual queue is constructed based on the following formula:

[0211] Among them, Z t is the delayed virtual queue with time t; Z t+1 is the delayed virtual queue at time t+1; ξ is a fixed parameter representing Q t >x tVirtual queue Z t The arrival rate of x t For queue Z t service rate;

[0212] Constrain the power queue according to the following formula: D max ≤R; R represents the delay time; D max Indicates the maximum queue delay of the power queue, Z max Indicates the maximum value corresponding to the delayed virtual queue.

[0213] Each module in the above-mentioned power grid dispatching device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the power equipment in the form of hardware, or can be stored in the memory in the power equipment in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0214] In an exemplary embodiment, a power device is provided. The power device may be a server, and its internal structure diagram may be as shown in FIG. Figure 5 As shown. The power device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the power device is used to provide computing and control capabilities. The memory of the power device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the power device is used to store data required for executing the power grid dispatching method, such as power generation information, air conditioning power consumption information, etc. The input / output interface of the power device is used to exchange information between the processor and an external device. The communication interface of the power device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a power grid dispatching method is implemented.

[0215] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present application, and does not constitute a limitation on the power equipment to which the scheme of the present application is applied. The specific power equipment may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0216] In an exemplary embodiment, an electric power device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0217] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0218] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0219] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0220] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0221] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A power grid dispatching method, characterized in that: include: Determine power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; Determine the power storage capacity of the power grid according to the power generation information; and construct a power supply control virtual queue based on the power storage capacity; Determine the air conditioning power usage information required to make the indoor temperature within the target temperature range; and construct an indoor temperature virtual queue based on the air conditioning power usage information; Based on the change of electricity price over time, determine the delay time required to wait for the current electricity price to be lower than the preset electricity price, and the charging amount required for the electric vehicle corresponding to the delay time; and construct an electric power queue corresponding to the charging of the electric vehicle according to the charging amount; construct a delayed virtual queue corresponding to the electric power queue, and constrain the electric power queue according to the delay time and the delayed virtual queue; Constructing a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue; Determining an expected value of the Lyapunov function based on time variation; Determining drift and penalty terms according to the expected value; According to the drift plus penalty item, the power grid is dispatched with the goal of meeting electricity demand and reducing electricity costs.

2. The method according to claim 1, characterized in that: The method further comprises: Determine the start and stop time of the air conditioner according to the distribution of indoor personnel; Constructing a total estimated cost function based on the start and stop time of the air conditioner and the change of electricity price over time; Determining the drift and penalty items according to the expected value includes: The drift and penalty terms are determined based on the expected value and the total predicted cost function.

3. The method according to claim 1, characterized in that The constructing of a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue includes: Among them, H t Q is the indoor temperature virtual queue; t is the power queue; Z t is the delayed virtual queue; K t A virtual queue is controlled for the power supply.

4. The method according to claim 1, characterized in that: The air conditioner power usage information includes air conditioner input power; and constructing an indoor temperature virtual queue according to the air conditioner power usage information includes: The indoor temperature under air conditioning is dynamically calculated based on the following formula: Among them, T t is the indoor temperature at time t; T t+1 is the indoor temperature at time t+1; is the outdoor temperature at time t; η is the thermal efficiency; A is the thermal conductivity; ω is the time constant; ε = e -τ / ω ;e t is the input power of the air conditioner at time t; Based on the first calculation formula and the second calculation formula, a virtual indoor temperature queue H is constructed. t ; The indoor temperature virtual queue H t Corresponding to the change of indoor temperature: The first calculation formula is: t =T t +Γ, where Γ is a constant term; The second calculation formula is H t Dynamic calculation formula: Among them, T out is the outdoor temperature.

5. The method according to claim 1, characterized in that The step of constructing a power queue corresponding to the charging of the electric vehicle according to the charging amount includes: According to the following calculation formula, the power queue Q corresponding to the electric vehicle charging is constructed t : Q t+1 =max[Q t -x t ,0]+a t ; Among them, x t and a t are the service rate and arrival rate of the power queue respectively; x max For x t The highest value, x max ≥a max , so that the queue remains stable; 0≤x t ≤min{x max , Q t }, so that x t Not greater than the power queue Q t of charge.

6. The method according to any one of claims 1 to 5, characterized in that The constructing of a delayed virtual queue corresponding to the power queue, and constraining the power queue according to the delay time and the delayed virtual queue, comprises: The delayed virtual queue is constructed based on the following formula: Among them, Z t is the delayed virtual queue at time t; Z t+1 is the delayed virtual queue at time t+1; ξ is a fixed parameter representing Q t >x t Virtual queue Z t The arrival rate of x t For queue Z t service rate; The power queue is constrained according to the following formula: D max ≤R; Wherein, R represents the delay time; D max represents the maximum queuing delay of the power queue, Z max Indicates the maximum value corresponding to the delayed virtual queue.

7. A power grid dispatching device, characterized in that: The device comprises: A queue construction module is used to determine the power generation information of the power grid; the power generation information includes photovoltaic power generation information and wind power generation information; determine the power storage capacity of the power grid according to the power generation information; and construct a power supply control virtual queue based on the power storage capacity; determine the air conditioning power consumption information required to make the indoor temperature within the target temperature range; and construct an indoor temperature virtual queue based on the air conditioning power consumption information; determine the delay time required to wait for the current power price to be lower than the preset power price based on the change of power price over time, and the charging amount required for the electric vehicle corresponding to the delay time; and construct a power queue corresponding to the charging of the electric vehicle according to the charging amount; and construct a delay virtual queue according to the delay time to constrain the power queue; A determination module, configured to construct a Lyapunov function according to the power supply control virtual queue, the indoor temperature virtual queue, the power queue and the delay virtual queue; determine an expected value of the Lyapunov function based on time variation; and determine a drift and a penalty term according to the expected value; The scheduling module is used to perform power grid scheduling based on the drift plus penalty item to meet the power demand and reduce the power cost.

8. An electric power device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images