Frequency safety and operation adequacy coordinated day-ahead optimization scheduling method

Abstract

The invention provides a day-ahead optimization scheduling method for coordinating frequency safety and operation adequacy. The method comprises the following steps: acquiring power data to construct a model constraint condition; the model constraint conditions at least comprise a frequency safety constraint condition and an operation adequacy constraint condition, and constructing a day-ahead optimization scheduling model of the power system according to the model constraint conditions; and solving the joint scheduling model to obtain a scheduling plan. According to the method, a frequency deviation integral index is introduced to construct a frequency security constraint; aiming at adequacy requirements, establishing adequacy and balance constraint conditions suitable for power grid operation control, constructing an optimal scheduling model, and solving a scheduling plan; the method has universality, can be applied to an optimization model of unit combination and economic dispatching, can give consideration to the safety and adequacy of the power grid frequency, effectively improves the safety and adequacy of the power grid, and has practical significance in the aspect of participation of source-load-storage multi-type resources in main grid optimization dispatching.

Description

Technical Field

[0001] The present invention relates to the technical field of joint dispatching of electric power systems, and in particular to a day-ahead optimization dispatching method for coordinating frequency safety and operation margin of a new energy power grid. Background Art

[0002] Renewable energy refers to energy that can be continuously regenerated in nature and utilized by existing technologies, such as solar energy, wind energy, hydropower, biomass energy, geothermal energy, etc. The greatest advantage of renewable energy is its sustainability, which enables renewable energy to meet human energy needs in the long term without facing the problem of exhaustion like fossil fuels; and the impact of renewable energy on the environment during production and use is relatively small, reducing the environmental problems caused by the exploitation and use of traditional energy.

[0003] Based on the advantages of renewable energy, as the technology matures, it has been connected to the existing power grid on a large scale, changing the traditional energy architecture. However, as the proportion of renewable energy increases, maintaining system balance becomes increasingly challenging. Factors such as the uncertainty of renewable energy, rising electricity demand, and insufficient inertia of the power system have exacerbated the temporal and spatial mismatch between supply and demand, increasing the risk of low-frequency events and insufficient redundancy in the power grid.

[0004] Therefore, in order to build a new power system, it is necessary to fully tap the system's flexibility and demand-side resources, which is conducive to the coordinated development and scientific allocation of various resources, and can also improve the system's operating efficiency and the comprehensive benefits of power development. Furthermore, in reality, when conducting joint optimization of the main grid's source-load-storage resources on the day before, it is necessary to take into account the grid frequency security and adequacy requirements at the same time.

[0005] Among them, frequency security is mainly evaluated through the dynamic frequency response process of the power system. The key indicators of frequency security include the rate of change of frequency (RoCoF), the lowest frequency point and the quasi-steady-state frequency. In order to ensure sufficient inertia and primary frequency regulation (PFR) resources in the power system, the existing technology proposes to incorporate frequency security constraints into unit commitment and economic dispatch. Based on this, the current methods for constructing frequency security constraints commonly include:

[0006] 1. Complete dynamic frequency constraint. The analytical expressions of RoCoF, the lowest frequency point and the quasi-steady-state frequency can be derived. However, the results derived by this method are all high-order nonlinear and require complex linearization techniques (such as piecewise linearization and inner approximation). These methods are too sophisticated to be applied to a variety of heterogeneous resources.

[0007] 2. Discrete dynamic frequency constraints, discretize the frequency and unit PFR power in sections; however, the high-precision model of this method requires an extremely short time step, which significantly increases the computational complexity;

[0008] 3. Simplified dynamic frequency constraint, based on the assumption that the PFR resource power is a linear ramp output, derives the expression of the lowest point of the system frequency, which is suitable for the optimization model of large-scale heterogeneous resources.

[0009] Further analysis shows that due to the difficulty of traditional thermal power to cope with power shortages in extreme events, there is a growing research on other emerging frequency regulation resources, including renewable energy, energy storage devices (such as pumped storage devices, battery energy storage) and demand response (such as temperature control loads, electric vehicles) to improve the system frequency response capability.

[0010] However, common sudden power shortages not only lead to frequency insecurity, but also reduce the adequacy of the power grid. Therefore, adequacy indicators are introduced at this stage to evaluate the stability of the power generation system. However, the existing adequacy indicators, such as load loss probability and expected power shortage, are all based on an annual time scale and are not suitable for unit combination and economic dispatch problems. Few studies explicitly construct adequacy indicators and apply them to dispatch problems. Most studies indirectly improve adequacy by introducing an objective function that monetizes adequacy risk, without explicitly proposing adequacy constraints in the optimization model.

[0011] In summary, it is also necessary to provide a scheduling method for the day-ahead joint scheduling of the main grid source-load-storage resources to effectively improve the security and redundancy of the power grid. Summary of the invention

[0012] In view of the problems existing in the prior art, the present invention provides a day-ahead optimization scheduling method which has simple steps and can take into account the coordination between frequency safety and operation margin.

[0013] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0014] The present invention provides a day-ahead optimization scheduling method for coordinating frequency safety and operation margin, which comprises the following steps:

[0015] Collect power data of power system;

[0016] constructing model constraints based on the power data;

[0017] The model constraints include at least frequency safety constraints and operation margin constraints;

[0018] The frequency safety constraint condition at least includes a frequency deviation integral constraint condition;

[0019] The operation margin constraint condition is a numerical constraint condition of the operation margin; the operation margin is the difference between the power and the reserve capacity on the generation side and the power and the reserve capacity on the user side of the power system;

[0020] According to the model constraints, constructing a day-ahead dispatch model of the power system with the goal of minimizing the cost of power shortage events;

[0021] Solve the day-ahead scheduling model and obtain a scheduling plan.

[0022] Optionally, the power data includes a topological map of the transmission network, line data, node data and unit data.

[0023] Optionally, the process of solving the frequency deviation integral constraint condition includes:

[0024] Solving the frequency deviation integral using the power data;

[0025] A threshold is set based on an operating condition of the power system, and the frequency deviation integral is less than or equal to the threshold.

[0026] Optionally, the process of solving the frequency deviation integral includes:

[0027] The power data includes primary frequency modulation data;

[0028] Obtaining the integral of the frequency deviation in the frequency modulation process and the linear expression of the decision variable based on the primary frequency modulation data;

[0029] The frequency deviation integral is obtained by time-integrating the frequency deviation according to the linear expression.

[0030] Optionally, the frequency safety constraint condition also includes a frequency initial change rate constraint condition and a quasi-steady-state frequency deviation constraint condition.

[0031] Optionally, the numerical constraint conditions of the operating margin include threshold constraints and / or linear constraints.

[0032] Optionally, the numerical constraint condition of the operating margin includes a first threshold constraint;

[0033] The threshold of the first threshold constraint is the minimum margin of the power system;

[0034] The operating margin is greater than or equal to the minimum margin.

[0035] Optionally, the minimum margin is proportional to the load of the power system.

[0036] Optionally, the numerical constraint condition of the operating margin further includes a second threshold constraint;

[0037] The threshold of the second threshold constraint is the maximum margin absolute deviation of the power system;

[0038] The average absolute deviation of the operating margin is less than or equal to the maximum margin absolute deviation.

[0039] Optionally, the numerical constraint condition of the operating margin includes a linear constraint;

[0040] The linear constraint is that the equilibrium value of the operating margin is less than or equal to the maximum margin absolute deviation of the power system;

[0041] The equilibrium value of the operating margin is a combined value of the linear relationship auxiliary variable and the mean absolute deviation of the operating margin.

[0042] Compared with the prior art, the present invention has the following beneficial effects:

[0043] The present invention constructs frequency safety constraints by introducing frequency deviation integral indicators; and according to the sufficiency requirements, establishes constraints on sufficiency and its balance applicable to power grid operation control, constructs an optimization scheduling model, and realizes the solution of scheduling plans; the method is universal and can be applied to the optimization models of unit combination and economic scheduling, and can take into account the frequency safety and sufficiency of the power grid, effectively improve the safety and sufficiency of the power grid, and has practical significance in the participation of multi-type resources of source, load and storage in the optimization scheduling of the main grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0045] Figure 1 is a flow chart of the method of the present invention;

[0046] Figure 2 It is a schematic diagram of the frequency safety index of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0049] It is worth noting that the methods used in the present invention are all conventional methods unless otherwise specified; the raw materials and devices used are all conventional commercially available products, and their sources are not specifically limited unless otherwise specified.

[0050] It should be noted that in order to facilitate understanding in the specific embodiments of the present invention, the method steps are described in a certain order, but those skilled in the art can change the order of the steps according to actual needs, and therefore this cannot be used as a limiting condition.

[0051] It should also be noted that one scenario in which the present invention is applicable is a local power system consisting of source-load-storage resources and a transmission network, and this is used as an example for explanation of a specific embodiment.

[0052] like Figure 1 As shown, this embodiment provides a joint optimization scheduling method for coordinating frequency security and operation margin, including the following steps:

[0053] First, the power data of the power system is collected, wherein the power data includes the topology diagram of the power transmission network, line data, source-load-storage resource node data and unit data of the power system, and constitutes the basic data for the implementation of the following method.

[0054] Model constraints are constructed based on the above power data. The model constraints include some basic unit operation constraints and DC power flow constraints, and on this basis, at least frequency safety constraints and operation margin constraints.

[0055] Furthermore, the frequency safety constraint condition includes at least a frequency deviation integral constraint condition.

[0056] The process of solving the frequency safety constraint condition includes:

[0057] Step S101: Introduce the frequency deviation integral index, and construct the linear frequency security constraint of the source-load-storage resource PFR process based on the RoCoF, quasi-steady-state frequency and frequency deviation integral index in the power data:

[0058] The power shortage in the power system leads to active power imbalance, which in turn causes the frequency to drop and initiates the PFR process. 0 At time t, the power fluctuation prompts the thermal power units, pumped storage units and flexible loads to provide PFR power until t 1The frequency at this moment stabilizes to a quasi-steady state. Please note that the time variable t in this step is the independent variable of the function and is a continuous quantity.

[0059] The frequency deviation Δf(t) during the PFR process can be modeled by a first-order differential equation, as shown in the power system swing equation:

[0060]

[0061] Where: H is the system inertia, D is the load damping rate, P D is the load demand level, ΔP L is the power fluctuation, P PFR (t) is the PFR power (MW) supplied to the system, and the adjustment formula is as follows:

[0062]

[0063] Where: and They represent the PFR power provided by the gth thermal power unit, the psth pumped storage unit and the flth flexible load respectively.

[0064] Assume that the PFR response power of the resource changes linearly with time and ignore the dead zone. The continuous function of the PFR provided by the thermal power unit, pumped storage unit and flexible load is as follows:

[0065]

[0066] Where: t g ,t ps and t fl They represent the response time of the gth thermal power unit, the psth pumped storage unit and the flth flexible load respectively; and is the PFR reserve capacity provided by the g-th thermal power unit and the fl-th flexible load; and is the PFR reserve capacity provided by the ps-th pumped storage unit in the power generation and pumping state, so Unlike thermal and pumped storage units, flexible loads such as electric vehicles and other demand response resources can quickly reduce power, providing a fast and precise response, which is usually accompanied by higher costs.

[0067] When the quasi-steady state is reached, dΔf(t) / dt=0 and Solving equation (1) yields Δf(t 1 ), represents the quasi-steady-state frequency deviation, denoted as Δf QSS , as shown below, where D′=DP D :

[0068]

[0069] The derivation process of the frequency deviation integral includes: constructing the power system swing equation based on the primary frequency regulation data, and obtaining the integral of the frequency deviation and the linear expression of the decision variable in the frequency regulation process. Therefore, in the PFR process, the integral of the frequency deviation and the decision variable are obtained through equation (1). 0 Time to t 1 Integrating at all times gives the frequency deviation integral F PFR , as shown below:

[0070]

[0071] Where t′ = t 1 -t 0 . Visible F PFR and Therefore, replacing the highly nonlinear frequency minimum point index with the frequency deviation integral index can simplify the optimization model and make the model more suitable for unit combination and economic scheduling application scenarios.

[0072] Frequency safety constraints also include the initial frequency change rate constraint and the quasi-steady-state frequency deviation constraint. Therefore, based on the swing equation (1), RoCoF is denoted as R cf , its expression and corresponding constraints are as follows:

[0073]

[0074] ΔP L ≤2HR cf,max (9)

[0075] Where: R cf,max is the maximum initial frequency change rate allowed by the system.

[0076] The quasi-steady-state frequency deviation can be calculated using equation (6), and the corresponding constraints are as follows:

[0077]

[0078] Where: Δf QSS,max It is the maximum quasi-steady-state frequency deviation allowed by the system.

[0079] like Figure 2 As shown, the frequency deviation integral calculated by formula (7) sets a threshold based on the operating conditions of the power system, and the frequency deviation integral is less than or equal to the threshold. The corresponding constraints are as follows:

[0080] F PFR ≤F PFR,max (11)

[0081] Where: F PFR,maxis the maximum frequency deviation integral allowed by the system.

[0082] By analyzing the expressions of the frequency safety constraints in the PFR process: Equations (9) to (11), it can be seen that there is no continuous variable t, which means that these constraints have captured the characteristics of the frequency response and can be applied to the optimization model.

[0083] The operation margin constraint condition is a numerical constraint condition of the operation margin. The operation margin is the difference between the power generation power and the load power of the power system. The specific steps are as follows:

[0084] Step S102: Comprehensively consider the main grid source-load-storage resource characteristics in the power data of the power system, and establish a linear calculation formula and constraints suitable for the adequacy and balance of power grid operation control:

[0085] When the power supply is insufficient to meet the demand, the power grid faces major challenges. The operational adequacy of the power grid is defined as the surplus between power generation and power consumption, that is, the difference between the power and spare capacity on the generation side and the power and spare capacity on the consumption side. Sufficient spare capacity must be achieved through the source-load-storage resources to cope with the mismatch between supply and demand. Note that in this step and subsequent steps, the time variable t is used as a subscript of the control variable, indicating the control period, and is a discrete quantity. Optionally, the numerical constraints of the operational adequacy include threshold constraints and balance constraints, so the calculation and constraints of the adequacy are as follows:

[0086]

[0087] Where: A t is the operating margin at time t, P d,t It is the power provided by the dth HVDC transmission line at time t. and They represent the predicted maximum power of the w-th wind turbine and the rl-th rigid load at time t respectively. The rigid load refers to the load that the power system must reliably supply. and They represent the generating power and pumping power of the ps-th pumped storage unit at time t, respectively. g,t and P fl,t They represent the power of the gth thermal power unit and the flth flexible load at time t respectively. and is the upper reserve capacity of the ps-th pumped storage unit during the pumping and power generation process at time t, and are the upper reserve capacity of the gth thermal power unit and the flth flexible load at time t. The numerical constraints of the operating margin include the first threshold constraint, It represents the minimum margin required by the system. It is a known quantity, and the minimum margin can be set to be proportional to the load of the power system, specifically a proportional value of the load.

[0088] To ensure that the model has linear characteristics, the numerical constraints of the operating margin also include a second threshold constraint. The design defines the margin balance index as the average absolute deviation of the margin, that is, the average of the absolute deviations of the margin from its mean. The calculation and constraints are as follows:

[0089]

[0090] A equ ≤A equ,max (15)

[0091] Where: The threshold of the second threshold constraint is the maximum margin absolute deviation of the power system, A equ is the mean absolute deviation of the operating margin, T is the total number of optimization cycles, is the average value of sufficiency, A equ,max is the maximum margin absolute deviation required by the system, and the average absolute deviation of the operating margin is less than or equal to the maximum margin absolute deviation required by the system.

[0092] Furthermore, the equilibrium constraint in the numerical constraint condition can be constructed based on the second threshold constraint and embodied in the form of a linear constraint. Specifically, the absolute value term in formula (14) can be converted into a linear constraint by introducing an auxiliary variable, that is, the equilibrium value of the operating margin is the combined value of the linear relationship auxiliary variable and the average absolute deviation of the operating margin.

[0093] According to the model constraints, a joint dispatch model of the power system with the goal of minimizing the cost of power shortage events is constructed. The specific steps are as follows:

[0094] Step S103: With the goal of minimizing the economic cost of coping with power shortage events, a unit combination and optimization scheduling model that coordinates grid frequency security and adequacy is constructed, and the scheduling plan of source-load-storage resources is obtained by solving the model:

[0095] The objective function is to minimize the risk mitigation cost, as follows:

[0096]

[0097] Where: and They are respectively the operating cost, start-up and shutdown cost, and standby cost of the g-th thermal power unit. and is the start-up and shutdown cost and standby cost of the ps-th pumped storage unit. is the load reduction cost of the flth flexible load. The specific calculation method of the cost is as follows:

[0098]

[0099] Where: a g ,b g are the power generation cost function parameters of the g-th thermal power unit respectively. and are the start-stop cost parameters of the g-th thermal power unit and the ps-th pumped storage unit respectively. and Provide cost parameters for upper reserve, lower reserve and PFR reserve capacity for the g-th thermal power unit respectively. and They respectively represent the cost parameters of the ps-th pumped storage unit providing upper reserve, lower reserve and PFR reserve capacity. and They represent the cost parameters of the upper reserve and PFR reserve capacity provided by the flth flexible load. g,t is the startup state of the g-th thermal power unit at time t, and They are the power generation and pumping states of the ps-th pumped storage unit at time t, respectively. They are all 0-1 variables, which are 1 when in this state and 0 when not in this state. It indicates the lower reserve of the g-th thermal power unit at time t, and are the lower reserve capacity of the ps-th pumped storage unit at time t in the pumping and power generation states. The decision variable set u,P,R,R PFR The definition is as follows:

[0100]

[0101] Where: It represents the lower reserve capacity of the fl-th flexible load at time t. Note that the four groups of variables related to the pumping and power generation status of the ps-th pumped storage unit are all positive and cannot be positive at the same time.

[0102] In summary, the constraints applicable to the model are divided into four categories: (1) operating constraints of thermal power units, pumped storage units and flexible loads; (2) network constraints and system backup requirements; (3) frequency security constraints; and (4) operating margin constraints, such as equations (13) and (15) in the aforementioned step S102.

[0103] Operation constraints are basic constraints and will not be described here. In view of the nonlinearity and complexity of the AC power flow model, the DC power flow model is used to verify the power balance and construct the network power flow constraints. When the frequency returns to its baseline value after the disturbance, the network power flow must be re-constrained. The system reserve constraint includes the constraints of the upper reserve and lower reserve capacity. The total system reserve capacity must exceed the minimum system reserve capacity requirement.

[0104] Based on the analysis of the frequency security constraints mentioned above, the constraints applicable to a single control cycle are described by equations (9) to (11). In order to incorporate these constraints into the optimization model, all time periods must be considered, so the discrete time dimension t is included in all constraints. In addition, additional frequency security constraints include: (i) system inertia, as shown in equation (27); (ii) PFR reserve capacity constraints, as shown in equations (28) to (31).

[0105]

[0106] In the formula, f 0 is the base frequency of the system, H g and H ps are the inertias of the g-th thermal power unit and the ps-th pumped storage unit, is the maximum generating power of the ps-th pumped storage unit.

[0107]

[0108] Where: η g , η ps and η fl They represent the maximum PFR reserve proportion of the g-th thermal power unit, the ps-th pumped storage unit and the fl-th flexible load respectively.

[0109] Finally, the day-ahead joint scheduling model of source-load-storage resources, that is, the optimization model obtained in this embodiment, is solved to obtain a scheduling plan; and the scheduling plan is executed on the source-load-storage resources.

[0110] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A day-ahead optimal scheduling method for coordinating frequency security and operating margin, characterized by: The steps include: Collect power data of power system; constructing model constraints based on the power data; The model constraints include at least frequency safety constraints and operation margin constraints; The frequency safety constraint condition at least includes a frequency deviation integral constraint condition; The operating margin constraint condition is a numerical constraint condition of the operating margin; The operation margin is the difference between the power and spare capacity of the power generation side and the power and spare capacity of the power consumption side of the power system; According to the model constraints, constructing a day-ahead dispatch model of the power system with the goal of minimizing the cost of power shortage events; Solve the day-ahead scheduling model and obtain a scheduling plan.

2. The method for day-ahead optimization scheduling based on coordination of frequency security and operation margin according to claim 1 is characterized by: The power data includes a topological diagram of the transmission network, line data, node data and unit data.

3. The method for day-ahead optimization scheduling for coordination of frequency security and operation margin according to claim 1 or 2, characterized in that: The process of solving the frequency deviation integral constraint condition includes: Solving the frequency deviation integral using the power data; A threshold is set based on an operating condition of the power system, and the frequency deviation integral is less than or equal to the threshold.

4. The method for day-ahead optimization scheduling for coordination of frequency security and operation margin according to claim 3 is characterized by: The process of solving the frequency deviation integral includes: The power data includes primary frequency modulation data; Obtaining the integral of the frequency deviation in the frequency modulation process and the linear expression of the decision variable based on the primary frequency modulation data; The frequency deviation integral is obtained by time-integrating the frequency deviation according to the linear expression.

5. The method for day-ahead optimization scheduling for coordination of frequency security and operation margin according to claim 3 is characterized by: The frequency safety constraint conditions also include a frequency initial change rate constraint condition and a quasi-steady-state frequency deviation constraint condition.

6. The method for day-ahead optimization scheduling for coordination of frequency security and operation margin according to claim 1, characterized in that: The numerical constraint condition of the operating margin includes a threshold constraint and / or a linear constraint.

7. The method for day-ahead optimal scheduling for coordination of frequency security and operation margin according to claim 6 is characterized by: The numerical constraint condition of the operating margin includes a first threshold constraint; The threshold of the first threshold constraint is the minimum margin of the power system; The operating margin is greater than or equal to the minimum margin.

8. The method for day-ahead optimal scheduling for coordination of frequency security and operation margin according to claim 7 is characterized by: The minimum margin is proportional to the load of the power system.

9. The method for day-ahead optimal scheduling for coordination of frequency security and operation margin according to claim 6, characterized in that: The numerical constraint condition of the operating margin also includes a second threshold constraint; The threshold of the second threshold constraint is the maximum margin absolute deviation of the power system; The average absolute deviation of the operating margin is less than or equal to the maximum margin absolute deviation.

10. The method for day-ahead optimization scheduling for coordination of frequency security and operation margin according to any one of claims 6 to 9, characterized in that: The numerical constraints of the operating margin include linear constraints; The linear constraint is that the equilibrium value of the operating margin is less than or equal to the maximum margin absolute deviation of the power system; The equilibrium value of the operating margin is a combined value of the linear relationship auxiliary variable and the mean absolute deviation of the operating margin.

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