A source-grid-load-storage collaborative regulation method and device under extreme weather, a terminal device, and a storage medium

Abstract

The application discloses a source-grid-load-storage collaborative regulation method and device under extreme weather, a terminal equipment and a storage medium. The method comprises the following steps: acquiring basic data of a power system, which comprises system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather and energy storage unit data; according to the basic data, taking the comprehensive minimum of the adjustable generator set power generation cost, the start-stop cost, the abandoned wind and light cost, the load shedding cost and the load transfer cost as the target, constructing a target function and load constraints, capacity constraints, node power balance constraints, unit technology constraints and energy storage constraints of the target function; solving the target function to generate the start state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charge-discharge state of the energy storage unit and the charge-discharge power of the energy storage unit when the comprehensive cost is minimum, and performing source-grid-load-storage collaborative regulation of the power system.

Description

Technical Field

[0001] The present invention relates to the field of power system control technology, and in particular to a source-grid-load-storage coordinated control method, device, terminal equipment and storage medium under extreme weather conditions. Background Art

[0002] In order to cope with extreme weather conditions, measures can be taken to ensure power supply security in all aspects of the power system's "source, grid, load, and storage." On the power supply side, this can be achieved by increasing the spare capacity of adjustable generator sets; on the grid side, cross-regional power transmission can be achieved through the "large grid"; on the load side, demand response can be used to improve power supply security in extreme weather conditions; and on the energy storage side, emergency response capabilities can be improved by building energy storage facilities. When regulating the power system, existing technologies ignore the impact of weather factors on the grid regulation process and only consider the influencing factors on one side for regulation. For example, only the factors on the load side are considered, and then a model is constructed with the goal of achieving minimum cost to solve the corresponding dispatching parameters for regulating the load side. This method does not take into account the uncertainty of both the source and load sides, as well as the impact of factors such as extreme weather on the power system regulation process, and is not applicable in extreme weather conditions. Summary of the Invention

[0003] The embodiments of the present invention provide a method, device, terminal equipment and storage medium for coordinated control of source, grid, load and storage under extreme weather conditions. The method is applicable to extreme weather conditions and can improve the control accuracy through comprehensive control, further improving the safety and stability of the power system operation under extreme weather conditions.

[0004] An embodiment of the present invention provides a method for coordinated control of power generation, grid, load and storage in extreme weather conditions, including:

[0005] Obtain basic data of the power system; wherein the basic data includes: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather conditions, and energy storage unit data;

[0006] Based on the basic data, an objective function of the source-grid-load-storage coordinated control model under extreme weather conditions is constructed with the goal of minimizing the combined power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power curtailment cost, the load shedding cost, and the load transfer cost; and load constraints, capacity constraints, node power balance constraints, unit technical constraints, and energy storage constraints of the objective function are constructed based on the basic data;

[0007] Solve the objective function under the constraints of load constraints, capacity constraints, node power balance constraints, unit technology constraints and energy storage constraints to generate a comprehensive minimum of adjustable generator set power generation cost, adjustable generator set start-stop cost, wind and light abandoned cost, load shedding cost and load transfer cost, the start state of the adjustable generator set, the output power of the adjustable generator set, the amount of load shedding, the amount of load transfer, the charge-discharge state of the energy storage unit and the charge-discharge power of the energy storage unit;

[0008] According to the start state of the adjustable generator set, the output power of the adjustable generator set, the amount of load shedding, the amount of load transfer, the charge-discharge state of the energy storage unit and the charge-discharge power of the energy storage unit, the source network load storage collaborative control of the power system is carried out.

[0009] Further, the objective function of the source network load storage collaborative control model is specific to:

[0010]

[0011]

[0012] Wherein, C t represents the objective function of the period t∈[1,T]; is the adjustable generator set power generation cost of the period t∈[1,T]; represents the adjustable generator set start-stop cost of the period t∈[1,T]; represents the wind and light abandoned cost of the period t∈[1,T]; represents the load shedding cost of the period t∈[1,T]; represents the load transfer cost of the period t∈[1,T]; represents the output of the adjustable generator set; N is the number of adjustable generator sets; a∈R N , b∈R N , c=diag{c i}∈R N×N , represents the power generation cost parameter; is the start cost of the i th adjustable generator set; is the stop cost of the i th adjustable generator set; is the start state of the i th adjustable generator set at the period t; is the stop state of the i th adjustable generator set at the period t;τ curt is the wind and light abandoned penalty cost coefficient; is the wind and light abandoned power of the new energy unit at time t; is the wind and light abandoned power of the new energy unit j at time t;M is the number of new energy units; is the load shedding cost of the non-interruptible load; and respectively, are the cut load cost of the first, second and third interruptible load; is the cut load amount of the non-interruptible load; and respectively, are the cut load amount of the first, second and third interruptible load; m is a node in the power system grid topology; Q is a set of nodes in the system; represents the load transfer amount of the load from time t to time t ′ .

[0013] Further, the load constraints include: non-transferable load constraints and transferable load constraints;

[0014] The non-transferable load constraints are:

[0015]

[0016] The transferable load constraints are:

[0017]

[0018] wherein, represents the proportion of non-interruptible load; and respectively, represent the proportion of the first, second and third interruptible load; represents the proportion of transferable load; represents the load prediction value of node m at time t.

[0019] Further, the capacity constraints are:

[0020]

[0021] wherein, p ws,jt is the cut-off probability of wind turbine group j at time t under wind speed ws; δ ws is the output threshold of wind turbine cut-off; β + is the risk tolerance of upper reserve capacity; β - is the risk tolerance of lower reserve capacity; is the sum of the maximum output of the started wind turbine groups connected to node m; is the sum of the minimum output of the started wind turbine groups connected to node m; represents the reserve capacity that needs to be increased when wind turbine group j is cut off at time t.

[0022] Further, the node power balance constraint is:

[0023]

[0024] Among them, θ m,t is the voltage phase angle of node m during period t; θ n,t is the voltage phase angle of node n during period t; x mn is the branch reactance between nodes m and n; is the maximum transmission power of branch mn; For the energy storage unit k∈S m The charge and discharge power at time t is When is discharge, When is charging; S m is the set of energy storage units connected to node m; is the output of adjustable generator set i at time t; E[·] represents the expectation of the random variable.

[0025] Furthermore, the unit technical constraints include: unit output constraints and unit climbing constraints;

[0026] The unit output constraint is determined according to the on / off state of the adjustable generator set, the output upper limit of the adjustable generator set and the output lower limit of the adjustable generator set;

[0027] The unit climbing constraint is determined according to the positive climbing limit of the adjustable generator set, the negative climbing limit of the adjustable generator set, and the switch state of the adjustable generator set.

[0028] Furthermore, the energy storage constraints include: energy storage capacity constraints and charge and discharge power constraints;

[0029] The energy storage capacity constraint is:

[0030]

[0031] The charge and discharge power constraints are:

[0032]

[0033] Among them, E k,t is the energy storage capacity of energy storage unit k at time t; is the charging efficiency of energy storage unit k; is the discharge efficiency of energy storage unit k; is the energy storage charging power of energy storage unit k at time t; is the energy storage discharge power of energy storage unit k at time t; is the upper limit of the discharge speed of the energy storage unit k; is the upper limit of the charging speed of energy storage unit k; is the lower limit of the energy storage capacity of energy storage unit k; is the upper limit of energy storage capacity of energy storage unit k.

[0034] Based on the above method embodiment, the present invention provides a corresponding device embodiment;

[0035] An embodiment of the present invention provides a source-grid-load-storage coordinated control device under extreme weather conditions, comprising: a data acquisition module, a model and constraint condition construction module, a model solving module, and a scheduling module;

[0036] The data acquisition module is used to acquire basic data of the power system; wherein the basic data includes: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather conditions, and energy storage unit data;

[0037] The model and constraint condition construction module is used to construct an objective function of the source-grid-load-storage coordinated control model under extreme weather conditions based on the basic data, with the goal of minimizing the combined power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost, and the load transfer cost; and construct the load constraint, capacity constraint, node power balance constraint, unit technical constraint, and energy storage constraint of the objective function based on the basic data;

[0038] The model solving module is used to solve the objective function under the constraints of load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints, and generate the starting state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging state of the energy storage unit and the charging and discharging power of the energy storage unit when the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost and the load transfer cost are comprehensively minimized;

[0039] The scheduling module is used to perform source-grid-load-storage coordinated regulation of the power system based on the startup status of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging status of the energy storage unit, and the charging and discharging power of the energy storage unit.

[0040] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the source-grid-load-storage coordinated control method under extreme weather conditions as described in the above-mentioned embodiment of the invention.

[0041] Another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the source-grid-load-storage coordinated control method under extreme weather conditions described in the above-mentioned embodiment of the invention.

[0042] The following beneficial effects are achieved by implementing the present invention:

[0043] The present invention provides a method, device, terminal equipment and storage medium for coordinated control of source, grid, load and storage under extreme weather conditions. The method obtains basic data of the power system and, based on the basic data of the power system, takes the comprehensive minimization of the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost and the load transfer cost as the goal, constructs the objective function of the coordinated control model of source, grid, load and storage under extreme weather conditions, as well as the load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints of the objective function, and then solves the objective function under the above constraints to obtain the startup state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging state of the energy storage unit and the charging and discharging state of the energy storage unit when the comprehensive cost is minimized. Electric power, and then the power system is coordinated with the source, grid, load and storage according to the solved data; because in extreme weather, the power system is mainly affected by the new energy generator set, by obtaining the source side adjustable generator set data and the new energy generator set data under extreme weather, the grid side system topology data and system power data, the load side system load data and the energy storage side energy storage unit data to construct the objective function of the source-grid-load-storage coordinated control model under extreme weather. While considering the impact of weather on the power system output, it can comprehensively analyze the situation on all sides of the power system, and then obtain the corresponding control results on each side. The coordinated control of the power system can be applicable to extreme weather, and the comprehensive control can improve the control accuracy, further improving the safety and stability of the power system in extreme weather. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of a method for coordinated control of source, grid, load and storage under extreme weather conditions provided by one embodiment of the present invention.

[0045] Figure 2 1 is a schematic diagram showing the relationship between operating costs and load shedding costs in different scenarios according to the proportion of transferable loads provided by an embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram of the relationship between the total startup time of a thermal power generating set and the proportion of transferable load provided by one embodiment of the present invention.

[0047] Figure 4 Schematic diagram of wind power, photovoltaic power generation and load prediction results and prediction error ranges provided by an embodiment of the present invention.

[0048] Figure 5 is a start-up capacity diagram under different weather scenarios provided by an embodiment of the present application.

[0049] Figure 6 is a structural diagram of a source-grid-load-storage collaborative regulation device under extreme weather provided by an embodiment of the present application. DETAILED DESCRIPTION

[0050] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0051] As Figure 1 shown, a source-grid-load-storage collaborative regulation method under extreme weather provided by an embodiment of the present application comprises:

[0052] Step S1: obtaining basic data of a power system; wherein the basic data comprises: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather, and energy storage set data;

[0053] Step S2: according to the basic data, constructing a target function of a source-grid-load-storage collaborative regulation model under extreme weather, with the objective of minimizing the comprehensive cost of adjustable generator set power generation, adjustable generator set start-stop cost, abandoned wind and light cost, load shedding cost, and load transfer cost; and based on the basic data, constructing load constraints, capacity constraints, node power balance constraints, unit technology constraints, and energy storage constraints of the target function;

[0054] Step S3: under the constraints of load constraints, capacity constraints, node power balance constraints, unit technology constraints, and energy storage constraints, solving the target function to generate the start state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charge-discharge state of the energy storage set, and the charge-discharge power of the energy storage set when the comprehensive cost of adjustable generator set power generation, adjustable generator set start-stop cost, abandoned wind and light cost, load shedding cost, and load transfer cost is minimized;

[0055] Step S4: performing source-grid-load-storage collaborative regulation of the power system according to the start state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charge-discharge state of the energy storage set, and the charge-discharge power of the energy storage set.

[0056] In step S1, basic data for the power system is obtained. This basic data includes system load data, system topology data, system power data, adjustable generator set data, data on new energy generator sets under extreme weather conditions, and energy storage unit data. System topology data primarily includes the number of system nodes and the connectivity between each node. System load data includes load shedding costs and load attributes. System power data includes the sum of the maximum output of active generator sets, the sum of the minimum output of active generator sets, the voltage phase angle of each node, the reactance of each branch, and the maximum power delivered by each branch. Adjustable generator set data includes the output of each adjustable generator set, power generation cost parameters, the deactivation cost of each adjustable generator set, the number of adjustable generator sets, the on / off status of each adjustable generator set, the upper and lower output limits of each adjustable generator set. Energy storage unit data includes the energy storage unit set, the energy storage capacity of each energy storage unit, the charge / discharge efficiency of each energy storage unit, the upper and lower charge / discharge speed limits of each energy storage unit, the upper and lower capacity limits of each energy storage unit. The data of new energy power generation units include: wind and solar power curtailment penalty cost coefficient, wind and solar power curtailment power, the number of new energy units, risk tolerance of upper reserve capacity and risk tolerance of lower reserve capacity.

[0057] It is necessary to add that, if Figure 2 As shown in the figure, it can be seen that increasing the proportion of transferable loads can effectively reduce the operating cost and load shedding cost in different scenarios, and the load transfer cost increases with the increase of load transfer amount; Figure 2 The scenarios given in the example include strong winds, typhoons and haze weather. Figure 3 As shown in (a), the total startup time of thermal power generating units changes with the proportion of transferable load. It can be seen that as the proportion of transferable load increases, the startup of thermal power units shows an increasing trend, and its main contribution to the growth comes from load transfer. At the same time, when the transferable load is low, due to the high wind speed in typhoon weather, a larger spare capacity is required, which makes the startup number of thermal power units higher than other weather scenarios. However, as the proportion of transferable load increases, part of the load is transferred to the off-peak period, which disperses the power supply pressure and makes the required startup amount consistent with other scenarios. Figure 3 (b) and Figure 3 As shown in (c), as the proportion of transferable load increases, the role of the load transfer mechanism increases, the peak shaving and valley filling effect becomes more obvious, and the load shedding amount gradually decreases until it reaches 0.

[0058] After obtaining the system load data, considering that the uncertainty of meteorological factors in extreme weather will affect the accuracy of load forecasting, it is necessary to classify the load and make the actual load at each moment obey the Gaussian distribution. Let m∈Q be the node in the power system grid topology, Q be the set of nodes in the system, is the load vector of node m, whose elements is the load forecast value of node m at time t, and this element obeys Gaussian distribution. At time t, the forecast amount of each type of load in node m can be distributed according to the proportion. Indicates the proportion of uninterruptible load; and They represent the proportion of the first-level interruptible load, the proportion of the second-level interruptible load, and the proportion of the third-level interruptible load respectively; represents the proportion of transferable load, and Need to meet: Non-interruptible loads correspond to extremely high load shedding costs Other interruptible but non-transferable loads correspond to different load shedding costs. In the present invention, the load shedding costs of interruptible loads are divided into three levels, namely, the load shedding costs of the first level interruptible loads Load shedding cost of the second-level interruptible load and load shedding costs for the third-level interruptible load

[0059] In addition to the impact on load, extreme weather also has an impact on new energy generators, mainly on wind turbines and photovoltaic generators. Figure 4 As shown in Figure 1, the forecast results and forecast error range of wind power, photovoltaic power generation and load are shown. According to the figure, it can be seen that under typhoons and strong winds, wind power generation has a higher probability of being cut off. Let G be the set of adjustable generator sets in the power system, H be the set of energy generator sets in the power system, G m represents the set of adjustable generators connected to node m, H m Represents the set of new energy generators connected to node m, i∈G m represents the adjustable generator set at node m, j∈H m Represents the renewable energy generator set at node m. Similar to the load, the output of renewable energy also satisfies the Gaussian distribution, where the wind power output Photovoltaic output The probability distribution of wind power output and photovoltaic output is affected by weather. Taking wind power output and photovoltaic output as independent random variables, the probability distribution of the total output of renewable energy generators can be obtained as: in:

[0060]

[0061] In addition, in extreme weather conditions, if the wind speed is too high, the wind turbine may be cut off, resulting in a situation where the wind turbine output is 0. For such situations, most current wind power output prediction models cannot directly judge. Moreover, since the reason for the wind turbine to be cut off is not only due to excessive wind speed, it is inaccurate to judge whether to cut off based solely on the wind speed and perform probabilistic modeling. Therefore, the present invention adopts Poisson distribution to count and fit the number of hours with zero output under different wind speed ranges in historical data, and obtains the probability that the wind turbine output is 0 under wind speed ws:

[0062] p ws =P ws (y ws ≤δ|s wind =ws);

[0063] Where δ is a very small number used to specify the output threshold of the wind turbine generator set. The wind speed ws can be divided into intervals, and we get ws∈{ws1,ws2,…}, where ws1 represents the wind speed range of [0,1], ws2 represents the wind speed range of [1,2], and so on to get the wind speed range in each interval. The unit of ws is m / s. In the above formula, p ws Indicates the probability of generator tripping within a certain wind speed range.

[0064] For step S2, based on the basic data, an objective function of the source-grid-load-storage coordinated regulation model under extreme weather conditions is constructed with the goal of minimizing the combined cost of power generation of the adjustable generator set, the cost of starting and stopping the adjustable generator set, the cost of curtailing wind and solar power, the cost of load shedding, and the cost of load transfer.

[0065] In a preferred embodiment, the objective function of the source-grid-load-storage coordinated control model is specifically:

[0066]

[0067]

[0068] Among them, C t represents the objective function for the period t∈[1,T]; is the power generation cost of the adjustable generator set in the period t∈[1,T]; represents the start-up and shutdown cost of the adjustable generator set during the period t∈[1,T]; represents the cost of curtailing wind and solar power during the period t∈[1,T]; represents the load shedding cost in the period t∈[1,T]; represents the load transfer cost in the period t∈[1,T]; Indicates the output of the adjustable generator set. N is the number of adjustable generator sets; a∈R N, b∈R N ,c=diag{c i}∈R N×N , represents the power generation cost parameter; is the startup cost of the i-th adjustable generator set; is the deactivation cost of the i-th adjustable generator set; is the starting state of the i-th adjustable generator set in time period t; is the disabled state of the i-th adjustable generator set in period t; τ curt Penalty cost coefficient for curtailing wind and solar power; is the abandoned wind and solar power of the new energy unit at time t; is the abandoned wind and solar power of renewable energy unit j at time t; M is the number of renewable energy units; is the load shedding cost of the non-interruptible load; and They are load shedding cost of first-level interruptible load, load shedding cost of second-level interruptible load and load shedding cost of third-level interruptible load respectively; The load shedding capacity for non-interruptible loads; and are the load shedding amount of the first-level interruptible load, the load shedding amount of the second-level interruptible load, and the load shedding amount of the third-level interruptible load respectively; m is a node in the power system grid topology; Q is the set of nodes in the system; Indicates that the load is transferred from time t to time t ′ The load transfer at the time.

[0069] Furthermore, load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints corresponding to the objective function are constructed.

[0070] In a preferred embodiment, the load constraints include: non-transferable load constraints and transferable load constraints;

[0071] The non-transferable load constraint is:

[0072]

[0073] For the transferable load, the load transferred out at each moment should be less than or equal to the transferable load at that moment. The transferable load constraint is:

[0074]

[0075] in, Indicates the proportion of uninterruptible load; and They represent the proportion of the first-level interruptible load, the proportion of the second-level interruptible load, and the proportion of the third-level interruptible load respectively; Indicates the proportion of transferable load; represents the load forecast value of node m at time t; t,t ′ ∈[1,T].

[0076] Preferably, considering the impact of extreme weather, considering that the total load random variable and the random variable of system energy processing are independent of each other, the total load of node m minus the net load of new energy output can be obtained as the random variable And the random variable Obey the Gaussian distribution, that is in:

[0077]

[0078] It is necessary to add that, if Figure 5 The figure shows the startup capacity under different weather scenarios. The green and blue curves represent the startup capacity under different scenarios at 95% and 99% confidence levels, respectively. The red and pink curves represent the startup capacity under the conservative and aggressive strategies, respectively. The conservative and aggressive strategies increase the reserve capacity to a fixed 10% and 2.5% of the load, respectively. The lower reserve capacity set by the conservative strategy results in a higher risk of load shedding during certain periods, while the higher reserve capacity set by the aggressive strategy requires more startup capacity, increasing system operating costs.

[0079] Since the risk of wind turbine curtailment is usually borne by the positive reserve capacity, the curtailment probability p of the wind turbine is considered. ws , we can know that the spare capacity caused by the additional cutting of the machine for:

[0080]

[0081] Further capacity constraint construction is carried out. In a preferred embodiment,

[0082]

[0083] Among them, p ws,jt is the probability of wind turbine j being tripped at time t under wind speed ws; ws is the output threshold of wind turbine generator set; β + is the constraint violation probability of the upper spare capacity, that is, the risk tolerance of the upper spare capacity; β - is the constraint violation probability of the lower spare capacity, that is, the risk tolerance of the lower spare capacity; is the sum of the maximum outputs of the enabled generator sets connected to node m, the sum of the minimum output of the on generator groups connected to node m, denotes the reserve capacity that wind turbine j needs to increase when it is shut down at time t.

[0084] Preferably, the above formula can be rewritten as an equivalent form when solving the model:

[0085]

[0086] In an extra-high voltage transmission line, the resistance is much smaller than the reactance, so the power flow of node m, n∈Q at time t can be approximated by the injection of active power as:

[0087]

[0088] where θ m,t is the voltage phase angle of node m at time t; θ n,t is the voltage phase angle of node n at time t; x mn is the branch reactance between nodes m and n; is the maximum transmission power of branch mn.

[0089] In a preferred embodiment, the above formula can be further combined to construct the node power balance constraint, specifically:

[0090]

[0091] where, is the charge and discharge power of energy storage unit k∈S m at time t, when is discharging, is charging; S m is the set of energy storage units connected to node m; is the output of adjustable generator unit i at time t; E[·] represents the expectation of a random variable.

[0092] In a power system, the start-stop state of an adjustable generator unit can be represented using a 0-1 decision variable, i.e. u i,t ∈{0,1} represents the start-stop state of generator unit i at time t, 0 represents the shutdown state, and 1 represents the startup state. Then, the start state of the i-th adjustable generator unit at time t and the shutdown state of the i-th adjustable generator unit at time t can be represented as:

[0093]

[0094] where, [·] + = max[·,0].

[0095] In a preferred embodiment, the unit technical constraints include: unit output constraints and unit climbing constraints; the unit output constraints are determined based on the switching state of the adjustable generator set, the output upper limit of the adjustable generator set, and the output lower limit of the adjustable generator set; the unit climbing constraints are determined based on the positive climbing limit of the adjustable generator set, the negative climbing limit of the adjustable generator set, and the switching state of the adjustable generator set.

[0096] Specifically, the technical constraints of the adjustable generator set mainly include output constraints and climbing constraints of the adjustable generator set.

[0097] The specific unit output constraints of the adjustable generator set are:

[0098]

[0099] in, is the lower limit of the output of the adjustable generator set i; is the upper limit of the output of the adjustable generator set i.

[0100] The specific climbing constraints of the adjustable generator set are:

[0101]

[0102] in, is the positive ramp limit of the adjustable generator set i; is the negative ramp limit of the adjustable generator set i.

[0103] In a preferred embodiment, the energy storage constraints include: energy storage capacity constraints and charge and discharge power constraints;

[0104] The energy storage capacity constraint is:

[0105]

[0106] The charge and discharge power constraints are:

[0107]

[0108] Among them, E k,t is the energy storage capacity of energy storage unit k at time t; is the charging efficiency of energy storage unit k; is the discharge efficiency of energy storage unit k; is the energy storage charging power of energy storage unit k at time t; is the energy storage discharge power of energy storage unit k at time t, is the upper limit of the discharge speed of the energy storage unit k; is the upper limit of the charging speed of energy storage unit k; is the lower limit of the energy storage capacity of energy storage unit k; is the upper limit of energy storage capacity of energy storage unit k.

[0109] For step S3, the mixed-integer linear programming (MILP) solution is used, and finally Python is used to call the IBM I LOG CPLEX solver to solve the objective function under the above constraints to obtain the starting state u of the adjustable generator set when the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar curtailment cost, the load shedding cost and the load transfer cost are minimized. i,t , adjustable generator set output power Load shedding Load transfer Energy storage unit charging and discharging status and charging power of energy storage unit and discharge power

[0110] For step S4, according to the starting state u of the adjustable generator set i,t Decide whether to start the traditional adjustable generator set, and then according to the output power of the adjustable generator set Adjust the output power of the adjustable generator set; according to the load shedding amount and load transfer Regulate the load side; determine the charging and discharging behavior of the energy storage unit according to the charging and discharging status of the energy storage unit, and and discharge power The energy storage unit is regulated under the corresponding charging and discharging behavior.

[0111] Based on the above method embodiments, the present invention provides corresponding device embodiments.

[0112] like Figure 6 As shown, an embodiment of the present invention provides a source-grid-load-storage coordinated control device under extreme weather conditions, comprising: a data acquisition module, a model and constraint condition construction module, a model solving module, and a scheduling module;

[0113] The data acquisition module is used to acquire basic data of the power system; wherein the basic data includes: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather conditions, and energy storage unit data;

[0114] The model and constraint condition construction module is used to construct an objective function of the source-grid-load-storage coordinated control model under extreme weather conditions based on the basic data, with the goal of minimizing the combined power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost, and the load transfer cost; and construct the load constraint, capacity constraint, node power balance constraint, unit technical constraint, and energy storage constraint of the objective function based on the basic data;

[0115] The model solving module is used to solve the objective function under the constraints of load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints, and generate the starting state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging state of the energy storage unit and the charging and discharging power of the energy storage unit when the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost and the load transfer cost are comprehensively minimized;

[0116] The scheduling module is used to perform source-grid-load-storage coordinated regulation of the power system based on the startup status of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging status of the energy storage unit, and the charging and discharging power of the energy storage unit.

[0117] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art can understand and implement the present invention without inventive effort.

[0118] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0119] Based on the above method embodiment, the present invention provides a corresponding terminal device embodiment.

[0120] An embodiment of the present invention provides a terminal device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a source-grid-load-storage coordinated control method under extreme weather conditions as described in any one of the present inventions.

[0121] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0122] The processor may be a central processing unit (CPU), other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal device, connecting various parts of the entire terminal device using various interfaces and lines.

[0123] The memory can be used to store the computer program, and the processor realizes various functions of the terminal device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Med i aCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0124] Based on the above method embodiment, the present invention provides a corresponding storage medium embodiment.

[0125] An embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute a source-grid-load-storage coordinated control method under extreme weather conditions as described in any one of the present inventions.

[0126] The storage medium is a computer-readable storage medium, and the computer program is stored in the computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. The computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium.

[0127] The above is a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for coordinated control of power generation, grid, load and storage in extreme weather conditions, characterized in that: include: Obtain basic data of the power system; wherein the basic data includes: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather conditions, and energy storage unit data; Based on the basic data, an objective function of the source-grid-load-storage coordinated control model under extreme weather conditions is constructed with the goal of minimizing the combined power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power curtailment cost, the load shedding cost, and the load transfer cost; and load constraints, capacity constraints, node power balance constraints, unit technical constraints, and energy storage constraints of the objective function are constructed based on the basic data; The objective function of the source-grid-load-storage coordinated control model is specifically: in, express Objective function of the time period; for The power generation cost of the adjustable generator set during the time period; express Adjustable start-up and shutdown costs of generator sets during different time periods; express The cost of curtailing wind and solar power during the period; express Load shedding cost during the period; express Load shifting costs during the time period; Indicates the output of the adjustable generator set; is the number of adjustable generator sets; , , , represents the power generation cost parameter; For the Start-up cost of an adjustable generator set; For the The outage cost of an adjustable generator set; For the adjustable generator sets in the time period The startup state; For the adjustable generator sets in the time period The deactivated state; Penalty cost coefficient for curtailing wind and solar power; For new energy units at all times of curtailed wind and solar power; For new energy units At the moment of curtailed wind and solar power; is the number of new energy units; is the load shedding cost of the non-interruptible load; 、 and They are load shedding cost of first-level interruptible load, load shedding cost of second-level interruptible load and load shedding cost of third-level interruptible load respectively; The load shedding capacity is the load that cannot be interrupted; 、 and They are the load shedding amount of the first-level interruptible load, the load shedding amount of the second-level interruptible load and the load shedding amount of the third-level interruptible load; is a node in the power system grid topology; is the set of nodes in the system; Indicates the load from Time shifts to The amount of load transfer at a given moment; Under the constraints of load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints, the objective function is solved to generate the startup state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging state of the energy storage unit and the charging and discharging power of the energy storage unit when the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost and the load transfer cost are minimized; The power system's source, grid, load and storage coordinated regulation is carried out according to the startup status of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging status of the energy storage unit and the charging and discharging power of the energy storage unit.

2. The method for coordinated control of source, grid, load and storage in extreme weather conditions according to claim 1, characterized in that: The load constraints include: non-transferable load constraints and transferable load constraints; The non-transferable load constraint is: The transferable load constraint is: in, Indicates the proportion of uninterruptible load; 、 and They represent the proportion of the first-level interruptible load, the proportion of the second-level interruptible load, and the proportion of the third-level interruptible load respectively; Indicates the proportion of transferable load; Representation node At the moment load forecast value.

3. The method for coordinated control of source, grid, load and storage in extreme weather conditions according to claim 2, characterized in that: The capacity constraints are: in, For wind speed Next, wind turbines exist The probability of machine disconnection at the moment; The output threshold for wind turbine generator set to be switched off; Risk tolerance for spare capacity; is the risk tolerance for the lower reserve capacity; For nodes The sum of the maximum outputs of the connected generator sets that are turned on; For nodes The sum of the minimum outputs of the connected generator sets that are turned on; Indicates wind turbine exist The spare capacity that needs to be added when cutting off the machine; For nodes The random variable obtained by subtracting the net load of renewable energy output from the total load.

4. The method for coordinated control of source, grid, load and storage in extreme weather conditions according to claim 2, characterized in that: The node power balance constraint is: in, for Time period node The voltage phase angle; for Time period node The voltage phase angle; For nodes and The branch reactance between For branch Maximum transmission power; For energy storage units exist The charge and discharge power at the moment When is discharge, When is charging; For nodes A collection of connected energy storage units; For adjustable generator sets exist The effort of every moment; represents the expectation of a random variable.

5. The method for coordinated control of source, grid, load and storage in extreme weather conditions according to claim 4, characterized in that: The unit technical constraints include: unit output constraints and unit climbing constraints; The unit output constraint is determined according to the on / off state of the adjustable generator set, the output upper limit of the adjustable generator set and the output lower limit of the adjustable generator set; The unit climbing constraint is determined according to the positive climbing limit of the adjustable generator set, the negative climbing limit of the adjustable generator set, and the switch state of the adjustable generator set.

6. The method for coordinated control of source, grid, load and storage in extreme weather conditions according to claim 5, characterized in that: The energy storage constraints include: energy storage capacity constraints and charge and discharge power constraints; The energy storage capacity constraint is: The charge and discharge power constraints are: in, For energy storage units exist Energy storage capacity at the moment; For energy storage units Charging efficiency; For energy storage units Discharge efficiency; For energy storage units exist Energy storage charging power at all times; For energy storage units exist Energy storage discharge power at the moment; For energy storage units The upper limit of discharge speed; For energy storage units The upper limit of charging speed; For energy storage units The lower limit of energy storage capacity; For energy storage units The upper limit of energy storage capacity.

7. A source-grid-load-storage coordinated control device under extreme weather conditions, characterized in that: include: Data acquisition module, model and constraint building module, model solving module and scheduling module; The data acquisition module is used to acquire basic data of the power system; wherein the basic data includes: system load data, system topology data, system power data, adjustable generator set data, new energy generator set data under extreme weather conditions, and energy storage unit data; The model and constraint condition construction module is used to construct an objective function of the source-grid-load-storage coordinated regulation model under extreme weather conditions based on the basic data, with the goal of minimizing the combined power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar curtailment cost, the load shedding cost, and the load transfer cost; and construct the load constraints, capacity constraints, node power balance constraints, unit technical constraints, and energy storage constraints of the objective function based on the basic data; wherein the objective function of the source-grid-load-storage coordinated regulation model is specifically: in, express Objective function of the time period; for The power generation cost of the adjustable generator set during the time period; express Adjustable start-up and shutdown costs of generator sets during different time periods; express The cost of curtailing wind and solar power during the period; express Load shedding cost during the period; express Load shifting costs during the time period; Indicates the output of the adjustable generator set; is the number of adjustable generator sets; , , , represents the power generation cost parameter; For the Start-up cost of an adjustable generator set; For the The outage cost of an adjustable generator set; For the adjustable generator sets in the time period The startup state; For the adjustable generator sets in the time period The deactivated state; Penalty cost coefficient for curtailing wind and solar power; For new energy units at all times of curtailed wind and solar power; For new energy units At the moment of curtailed wind and solar power; is the number of new energy units; is the load shedding cost of the non-interruptible load; 、 and They are load shedding cost of first-level interruptible load, load shedding cost of second-level interruptible load and load shedding cost of third-level interruptible load respectively; The load shedding capacity is the load that cannot be interrupted; 、 and They are the load shedding amount of the first-level interruptible load, the load shedding amount of the second-level interruptible load and the load shedding amount of the third-level interruptible load; is a node in the power system grid topology; is the set of nodes in the system; Indicates the load from Time shifts to The amount of load transfer at a given moment; The model solving module is used to solve the objective function under the constraints of load constraints, capacity constraints, node power balance constraints, unit technical constraints and energy storage constraints, and generate the starting state of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging state of the energy storage unit and the charging and discharging power of the energy storage unit when the power generation cost of the adjustable generator set, the start-up and shutdown cost of the adjustable generator set, the wind and solar power abandonment cost, the load shedding cost and the load transfer cost are comprehensively minimized; The scheduling module is used to perform source-grid-load-storage coordinated regulation of the power system based on the startup status of the adjustable generator set, the output power of the adjustable generator set, the load shedding amount, the load transfer amount, the charging and discharging status of the energy storage unit, and the charging and discharging power of the energy storage unit.

8. A terminal device, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a source-grid-load-storage coordinated control method under extreme weather conditions as described in any one of claims 1 to 6.

9. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein, when the computer program is running, the device where the storage medium is located is controlled to execute the source-grid-load-storage coordinated control method under extreme weather conditions as described in any one of claims 1 to 6.

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