Long-short-term coupling scheduling method for hybrid pumped storage power station

Abstract

The invention discloses a long and short term coupling scheduling method for a hybrid pumped storage power station, and belongs to the technical field of power station scheduling. According to the method, based on an existing medium-and-long-term reservoir optimization scheduling model, a long-and-short-term coupling scheduling model considering medium-and-long-term constraints and short-term operation characteristics of the hybrid pumped storage power station at the same time is constructed, a typical day is selected every month, and medium-and-long-term monthly scale constraints and short-term typical day constraints are incorporated into the model; the model comprises an objective function, medium and long term monthly scale constraints, short term typical day constraints and long and short term coupling constraints, nonlinear constraints are linearized and converted into a mixed integer linear programming problem, and the problem is solved by a gurobi solver. The method solves the problem that a traditional model is difficult to accurately describe a'water pumping-power generation 'mode, avoids the deviation of scheduling schemes of different time scales, guides the efficient operation of the hydropower station, improves the power generation benefit, and can be widely applied to the scheduling of the hybrid pumped storage power station.

Description

Technical Field

[0001] This invention relates to the field of reservoir scheduling technology, and in particular to a long-term and short-term coupled scheduling method for hybrid pumped storage power stations. Background Technology

[0002] Due to the intermittent and fluctuating nature of new energy sources, higher demands are placed on the stability of the power system, making the active development of energy storage an inevitable trend. Adding reversible units to conventional hydropower stations, transforming them into hybrid pumped storage power stations, eliminates the need for lengthy site selection and construction periods, and allows for rapid expansion of energy storage capacity. However, the introduction of reversible units alters the original operating mode of conventional hydropower stations. Accurately describing the application of the "pumping-generation" mode in the dispatch model to obtain precise reservoir dispatching schemes has become a critical issue that urgently needs to be addressed.

[0003] Depending on the scheduling cycle, reservoir optimization scheduling can be divided into medium- and long-term optimization scheduling and short-term optimization scheduling. Existing research mainly focuses on reservoir optimization scheduling for conventional hydropower stations, and medium- and long-term scheduling is often considered separately, or the medium- and long-term reservoir capacity process is used as the boundary for short-term scheduling. If this method is directly applied to hybrid pumped storage power stations, the medium- and long-term reservoir optimization scheduling model lacks the representation of the short-term "pumping-power generation" operating condition of hybrid pumped storage power stations, resulting in a scheduling scheme that is not globally optimal. Specifically, the medium- and long-term reservoir capacity boundary determines the daily outflow of hybrid pumped storage power stations, which in turn determines their daily pumping and power generation. If the short-term "pumping-power generation" operating condition is not considered in the medium- and long-term scheduling process, the resulting scheduling scheme cannot accurately reflect the actual daily operating needs of hybrid pumped storage power stations, making the established medium- and long-term scheduling boundary unable to effectively guide the optimal operation of the power station. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a long-term and short-term coupled scheduling method for hybrid pumped storage power stations. This method aims to solve the problem that, when conventional hydropower station reservoir optimization scheduling methods are applied to hybrid pumped storage power stations, the medium- and long-term reservoir optimization scheduling model lacks representation of the short-term "pumping-power generation" operating conditions, resulting in a non-globally optimal scheduling scheme, and the medium- and long-term scheduling boundary cannot effectively guide the optimal operation of the power station.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: A long-term and short-term coupled scheduling method for hybrid pumped storage power stations is proposed. Based on existing medium- and long-term reservoir optimization scheduling models, a long-term and short-term coupled scheduling model is constructed that simultaneously considers the medium- and long-term constraints and short-term operating characteristics of hybrid pumped storage power stations. By selecting a typical day each month as a representative, both the medium- and long-term monthly-scale constraints and the short-term typical day constraints of the hybrid pumped storage power station are incorporated into the model. The long-term and short-term coupled scheduling model includes an objective function, medium- and long-term monthly-scale constraints, short-term typical day constraints, and long-term and short-term coupled constraints. Nonlinear constraints are linearized, transforming the entire model into a mixed-integer linear programming problem, which is solved using the commercial Gurobi solver. The specific steps include: S1: Construct an objective function with the goal of maximizing power generation efficiency, introduce time-of-use pricing, and guide power plants to realize profits and peak shaving within a typical day; S2: Construct medium- and long-term monthly-scale constraints, including monthly water balance constraints, upper and lower limits of reservoir capacity constraints, and upper and lower limits of outflow constraints; S3: Construct short-term typical daily constraints, including water balance constraints between typical daily time periods, upper and lower limits constraints on reservoir capacity and outflow, constraints on the relationship between reservoir area and capacity, reservoir evaporation constraints, constraints on reservoir power generation and pumping head, constraints on the total number of generating units, constraints on unit operating status, constraints on power plant operating status, constraints on unit output characteristics, constraints on conventional unit operation restrictions, constraints on upper and lower limits constraints on unit flow and power, constraints on the duration of unit start-up / shutdown, constraints on the upper limit of the number of unit starts, constraints on reversible unit operating condition switching, constraints on the relationship between power plant output and unit output, constraints on power plant output fluctuation, constraints on channel capacity, and constraints on the relationship between time period output and power generation. S4: Construct long-term and short-term coupling constraints, including the relationship constraints between the beginning and end storage capacity of a typical day and the beginning and end storage capacity of the month, as well as the constraints on the connection between time period and monthly scale flow. S5. Linearize the nonlinear constraints in the model; S6. Given the inflow of water, use the inflow as the input to the long-term and short-term coupled scheduling model, determine the boundary conditions for the reservoir and generating units in the model, solve the model using the gurobi mixed-integer linear programming solver, and obtain the scheduling process of the reservoir.

[0006] Furthermore, the expression for the objective function in step S1 is: ; in, m and t These represent the month number and the time period number of a typical day, respectively. M and T These represent the total number of months and the total number of typical daily time periods, respectively. Real-time scheduling is generally done at 15-minute intervals, so we take... T =96; expressm Typical intraday period of the month t Electricity price, unit: yuan / MWh; express m Typical intraday period of the month t Electricity generation, unit: MWh; for m The number of days in a month.

[0007] Furthermore, the specific expression for the medium- to long-term monthly scale constraint mentioned in step S2 is as follows: 2a. Monthly water balance constraint: ; ; Inbound and outbound flow satisfy: ; Upper and lower reservoir capacity boundary constraints: ; in, and For months Reservoir capacity (upper and lower reservoirs), unit: m 3 ; and For months Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months Water loss due to evaporation, unit: m 3 / s; For months Water inflow to the upper reservoir, unit: m 3 / s; For months Time span, in seconds; and Given the initial and final storage capacities of the upper reservoir, typically set as the normal storage capacity, the unit is m. 3 ; The initial capacity of the given reservoir, in meters (m). 3 ; and For months Power generation flow and water discharge, unit: m³ 3 / s; 2b. Upper and lower limits of storage capacity constraints: ; in, and For months Initially, the upper and lower limits of the reservoir's capacity were given, in meters. 3 ; and For months Initial reservoir capacity limits, unit: m 3 ; 2c. Outbound flow upper and lower limit constraints: ; in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s.

[0008] Furthermore, the short-term typical day constraints include water balance constraints during typical day periods, upper and lower limits constraints on reservoir capacity and outflow, constraints on the relationship between reservoir area and capacity, reservoir evaporation constraints, constraints on reservoir power generation and pumping head, constraints on the total number of generating units, constraints on unit operating status, constraints on power plant operating status, constraints on unit output characteristics, constraints on conventional unit operation restrictions, upper and lower limits constraints on unit flow and power, constraints on the duration of unit start-up / shutdown, constraints on the upper limit of the number of unit starts, constraints on reversible unit operating condition switching, constraints on the relationship between power plant output and unit output, constraints on power plant output fluctuations, constraints on channel capacity, and constraints on the relationship between output and power generation during time periods.

[0009] Furthermore, the specific expression for the short-term typical day constraint mentioned in step S3 is as follows: (3a) Water balance constraints during typical daily periods: ; ; Inbound and outbound flow satisfy: ; in, and For months Typical day Reservoir capacity at the beginning of the period, for both the upper and lower reservoirs, in meters (m³). 3 ; and For months m Typical intraday period Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months m Typical intraday period Flow loss due to evaporation, unit: m 3 / s; The time span between time periods (15 minutes); For months m Typical intraday period Any unit n Power generation flow (including reversible and conventional units), unit: m³ 3 / s; For months m Typical intraday period Reversible unit Pumping flow rate, unit: m 3 / s; For months m Typical intraday period Wastewater, unit: m 3 / s; (3b) Upper and lower limits constraints on storage capacity and outbound flow: ; in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s; (3c) Constraints on the relationship between reservoir area and capacity: ; in, For months m Typical intraday period Reservoir area, unit: m 2 ; A function representing the relationship between reservoir area and reservoir capacity; (3d) Reservoir evaporation constraint: ; in, For months m Evaporation rate per unit area, expressed in m / s; (3e) Reservoir power generation and pumping head constraints: ; ; in, and Months Typical intraday period Water head during power generation and pumping, unit: m; This indicates the water level in front of the dam of the upper reservoir, determined by the reservoir capacity, in meters (m). This indicates the tailwater level determined by the outflow rate, in meters (m). This indicates the elevation of the pumping pipe installed in the lower reservoir, in meters (m). (3f) Total number of generating units constraint: ; in, , and These represent the total number of generating units, the number of conventional generating units, and the number of reversible generating units, respectively. (3g) Unit operating status constraints: ; Among them, integer variables (0 or 1) indicates the month. m Typical intraday period unit n The running status is 0, which indicates that it is not in this state, and 1 indicates that it is in this state; These represent three states: shutdown, power generation, and water pumping. (3h) Power plant operating status constraints: ; and These represent the subscripts for conventional units and reversible units, respectively. (3i) Unit output characteristic constraints; ; ; in, Indicates month m Typical intraday period unit n Power output, unit: MW; Indicates month m Typical intraday period Reversible unit Pumping power, unit: MW; Indicates the unit n The relationship between power output, head, and power generation flow rate; Indicates reversible unit The relationship between pumping power, head, and pumping flow rate; (3j) Operating constraints of conventional units: ; (3k) Unit flow and power upper and lower limit constraints: ; ; ; ; in, and Indicates the unit n Upper and lower limits of power generation flow rate, unit: m³ 3 / s; and Indicates reversible unit Upper and lower limits of pumping flow rate, unit: m 3 / s; and Indicates the unit n Upper and lower limits of output, unit: MW; and Indicates reversible unit Upper and lower limits of pumping power, unit: MW; (3l) Unit start / stop duration constraints: ; ; ; and satisfy: ; Among them, integer variables Indicates that the unit is Changes in state at the beginning of the period These respectively represent the unit's state from (shutdown to power generation, shutdown to pumping while maintaining the same state, power generation to shutdown, and pumping to shutdown); , and These represent the number of time periods during which the generating unit remains in at least the off, generating, or pumping states, respectively. (3m) Maximum number of unit start-ups: ; in Indicates the unit n Maximum number of startups allowed; (3n) Reversible unit operating condition switching constraints: ; (3o) Constraints on the relationship between power plant output and unit output: ; in, This indicates the total output of the power plant, in MW. Waste electricity generated by the power plant, unit: MW; (3p) Power plant output fluctuation constraints: ; in, It represents the absolute value of the output fluctuation over a period of time; This indicates the maximum allowable power output fluctuation within a given time period; (3q) Channel capacity constraint: ; in This indicates the upper limit of the transmission line channel capacity, which is generally set as the total installed capacity of the power plant; (3r) Constraints on the relationship between power output and power generation during the time period: .

[0010] Furthermore, the specific expression for the long-term and short-term coupling constraints mentioned in step S4 is as follows: (4a) Constraints on the relationship between the beginning and ending storage capacity of a typical day and the beginning and ending storage capacity of that month: When the number of days in that month When it is even: ; ; When the number of days in that month When it is an odd number: ; ; The initial and final reservoir capacities on a typical day are calculated using the same interpolation method. (4b) Constraints on the connection between time period and monthly scale flow: ; ; .

[0011] Furthermore, the nonlinear constraints mentioned in step S5 include constraints on the relationship between reservoir surface area and reservoir capacity, constraints on reservoir power generation and pumping head, constraints on the duration of unit start-up / shutdown, and constraints on unit output characteristics. The constraints on the relationship between reservoir surface area and reservoir capacity, and the constraints on reservoir power generation and pumping head, are linearized through piecewise linear approximation. The linearization methods for the constraints on the duration of unit start-up / shutdown and the constraints on unit output characteristics are as follows: (5a) Linearization of unit start / stop duration constraints: The unit start / stop duration constraint is equivalently replaced with a linear constraint: ; ; ; (5b) Linearization of unit output characteristic constraints: The nonlinear problem of turbine unit output characteristics is addressed through an iterative head process. Under a fixed head, a linear fit is performed on the relationship between output and flow rate to obtain linear constraints. ; ; in, and Indicates water head The slope of the fitted line; and Indicates water head The intercept of the fitted line.

[0012] Furthermore, the head iteration process is as follows: the initial head value is set to the monthly average value, a mixed integer linear programming model containing linear constraints on unit output characteristics but excluding nonlinear constraints on unit output characteristics is solved, the change of the target is judged, if the target is improved, the head is updated, otherwise the reservoir capacity range is reduced, and the above process is repeated until the head converges to be sufficiently close to the previous solution.

[0013] Furthermore, in step S6, the inflow of water to the upper reservoir is included in the monthly water balance constraint; the upper and lower limits of reservoir capacity are included in the upper and lower limits of reservoir capacity constraint; the upper and lower limits of outflow are included in the upper and lower limits of outflow; the unit state holding time parameter is included in the linear constraint of unit start / stop duration; and the maximum number of unit starts is included in the upper limit constraint of unit start times. The boundary conditions include the upper and lower limits of output and the upper and lower limits of power generation flow in the constraints of unit flow and power.

[0014] Furthermore, the reservoir scheduling process in step S6 includes the medium- and long-term reservoir scheduling process and the reservoir scheduling process on typical days each month; the medium- and long-term reservoir scheduling process is the water level and output flow of the reservoir each month; the reservoir scheduling process on typical days each month is the output process of each unit in 96 time periods within a day.

[0015] Compared with the prior art, the present invention has the following beneficial effects: (1) By constructing a long-term and short-term coupled scheduling model that simultaneously considers the medium- and long-term constraints and short-term operating characteristics of hybrid pumped storage power stations, the medium- and long-term monthly scale constraints and short-term typical daily constraints are simultaneously incorporated into the model, effectively solving the problem that traditional medium- and long-term reservoir optimization scheduling models cannot accurately characterize the pumping-power generation mode of hybrid pumped storage power stations.

[0016] (2) By selecting a typical day each month, the monthly-scale indicators of medium- and long-term reservoir optimization scheduling are evaluated, while fully considering the pumping-power generation characteristics of the hybrid pumped storage power station on the typical day. This avoids deviations between scheduling schemes at different time scales and can effectively guide the efficient operation of the hydropower station. Furthermore, the nonlinear constraints in the model are reasonably linearized and transformed into a mixed-integer linear programming problem, which can be solved using commercial solvers such as gurobi. The solution is convenient and the results are reliable, and the globally optimal scheduling scheme can be obtained, thereby improving the power generation efficiency of the hybrid pumped storage power station. Attached Figure Description

[0017] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 A fitted graph showing the relationship between unit output and power generation flow rate; Figure 2 Here is a flowchart of the head iteration process; Figure 3 A typical daily power generation process diagram of a hybrid pumped storage power station under a long-term and short-term coupled scheduling model; Figure 4 A typical daily power generation process diagram of a hybrid pumped storage power station under a nested long-term and short-term scheduling model; Figure 5 This is a flowchart of the long-term and short-term coupled scheduling model. Detailed Implementation

[0018] To more clearly illustrate the technical solution of the present invention, the embodiments are described below with reference to the accompanying drawings. However, these drawings are only used to illustrate the principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0019] This invention provides a long-term and short-term coupled scheduling method for hybrid pumped storage power stations. Based on existing medium- and long-term reservoir optimization scheduling models, this method constructs a long-term and short-term coupled scheduling model that simultaneously considers the medium- and long-term constraints and short-term operational characteristics of the hybrid pumped storage power station. By selecting a typical day each month as a representative, both the medium- and long-term monthly-scale constraints and the short-term typical day constraints of the hybrid pumped storage power station are incorporated into the model. The long-term and short-term coupled scheduling model includes an objective function, medium- and long-term monthly-scale constraints, short-term typical day constraints, and long-term and short-term coupled constraints. The nonlinear constraints are appropriately linearized, transforming the entire model into a mixed-integer linear programming problem, which can then be solved using the commercial Gurobi solver. Figure 5 As shown, the specific steps are as follows: 1. Construct the objective function: Low-price pumping followed by high-price power generation is a common profit-generating strategy for pumped-storage hydroelectric power plants, and it is equally applicable to hybrid pumped-storage power plants. Therefore, the model introduces time-of-use pricing, with the objective function of maximizing power generation efficiency, to guide the power plant to realize profit generation and peak shaving within a typical day. (1) in, m and t These represent the month number and the time period number of a typical day, respectively. M and T These represent the total number of months and the total number of typical daily time periods, respectively. Real-time scheduling is generally done at 15-minute intervals, so we take... T =96; express m Typical intraday period of the month t Electricity price, unit: yuan / MWh; express m Typical intraday period of the month t Electricity generation, unit: MWh; for m The number of days in a month.

[0020] 2. Construct medium- to long-term monthly scale constraints, including the following constraints: (1) Monthly water balance constraint A hybrid pumped-storage power station consists of an upper reservoir and a lower reservoir, with the main consideration being the water balance between the two reservoirs. During power generation, water is released from the upper reservoir to the lower reservoir, converting gravitational potential energy into electrical energy; during energy storage, water is pumped from the lower reservoir to the upper reservoir, converting electrical energy into stored gravitational potential energy.

[0021] (2) (3) Inbound and outbound flow satisfy: (4) The upper reservoir has a larger adjustable capacity, and its initial and final capacity boundaries are constrained to ensure the sustainability of power generation; while the lower reservoir is generally a daily regulating reservoir, and only its initial capacity boundary is constrained.

[0022] (5) in, and For months Reservoir capacity (upper and lower reservoirs), unit: m 3 ; and For months Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months Water loss due to evaporation, unit: m 3 / s; For months Water inflow to the upper reservoir, unit: m 3 / s; For months Time span, in seconds; and Given the initial and final storage capacities of the upper reservoir, typically set as the normal storage capacity, the unit is m. 3 ; The initial capacity of the given reservoir, in meters (m). 3 ; and For months Power generation flow and water discharge, unit: m³ 3 / s.

[0023] (2) Upper and lower limits of storage capacity constraints

[0024] in, and For months Initially, the upper and lower limits of the reservoir's capacity were given, in meters. 3 ; and For months Initial reservoir capacity limits, unit: m 3 .

[0025] (3) Upper and lower limits of outbound flow

[0026] in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s.

[0027] 3. Construct short-term typical daily constraints, including: (1) Water balance constraints during typical daily periods (10) (11) Inbound and outbound flow satisfy: (12) in, and For months Typical day Reservoir capacity at the beginning of the period, for both the upper and lower reservoirs, in meters (m³). 3 ; and For months m Typical intraday period Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months m Typical intraday period Flow loss due to evaporation, unit: m 3 / s; The time span between time periods (15 minutes); For months m Typical intraday period Any unit n Power generation flow (including reversible and conventional units), unit: m³ 3 / s; For months m Typical intraday period Reversible unit Pumping flow rate, unit: m 3 / s; For months m Typical intraday period Wastewater, unit: m 3 / s.

[0028] (2) Upper and lower limits of storage capacity and outbound flow

[0029] in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s.

[0030] (3) Relationship between reservoir area and reservoir capacity (17) in, For months m Typical intraday period Reservoir area, unit: m 2 ; A function representing the relationship between the reservoir area and its capacity.

[0031] (4) Reservoir evaporation (18) in, For months m Evaporation rate per unit area, expressed in m / s.

[0032] (5) Reservoir power generation and pumping head (19) (20) in, and Months Typical intraday period Water head during power generation and pumping, unit: m; This indicates the water level in front of the dam of the upper reservoir, determined by the reservoir capacity, in meters (m). This indicates the tailwater level determined by the outflow rate, in meters (m). This indicates the elevation of the pumping pipe installed in the lower reservoir, in meters (m).

[0033] (6) Total number of generating units constraint (twenty one) in, , and These represent the total number of generating units, the number of conventional generating units, and the number of reversible generating units, respectively.

[0034] (7) The unit can only be in one of the pumping / generating states. (twenty two) Among them, integer variables (0 or 1) indicates the month. m Typical intraday period unit n The running status is 0, which indicates that it is not in this state, and 1 indicates that it is in this state; These represent three states: shutdown, power generation, and water pumping. (8) The power station can only be in one of the following states: pumping water or generating electricity. (twenty three) and These represent the subscripts for conventional units and reversible units, respectively.

[0035] (9) Unit output characteristics (twenty four) (25) in, Indicates month m Typical intraday period unit n Power output, unit: MW; Indicates month m Typical intraday period Reversible unit Pumping power, unit: MW; Indicates the unit n The relationship between power output, head, and power generation flow rate; Indicates reversible unit The relationship between pumping power, head, and flow rate.

[0036] (10) Conventional units cannot pump water. (26) (11) Upper and lower limits of unit power generation flow, pumping flow, output, and pumping power (27) (28) (29) (30) in, and Indicates the unit n Upper and lower limits of power generation flow rate, unit: m3 / s; and Indicates reversible unit Upper and lower limits of pumping flow rate, unit: m 3 / s; and Indicates the unit n Upper and lower limits of output, unit: MW; and Indicates reversible unit Upper and lower limits of pumping power, unit: MW.

[0037] (12) Unit start-up / shutdown duration constraints (31) (32) (33) and satisfy: (34) Among them, integer variables Indicates that the unit is Changes in state at the beginning of the period These respectively represent the unit's state from (shutdown to power generation, shutdown to pumping while maintaining the same state, power generation to shutdown, and pumping to shutdown); , and These represent the number of time periods during which the unit remains in at least the off, power generation, and pumping states.

[0038] (13) Maximum number of unit start-ups (35) in Indicates the unit n The maximum number of startups allowed.

[0039] (14) Reversible units need to undergo a shutdown when switching between pumping and power generation modes. (36) (15) Relationship between power plant output and unit output (37) in, This indicates the total output of the power plant, in MW. The abandoned electricity generated by the power plant, in MW.

[0040] (16) Power output fluctuation constraints (38) in, It represents the absolute value of the output fluctuation over a period of time; This indicates the maximum allowable power output fluctuation during a given time period.

[0041] (17) Channel capacity constraints (39) in This indicates the upper limit of the transmission line channel capacity, which is generally set as the total installed capacity of the power plant.

[0042] (18) Relationship between power output and electricity generation during a given time period (40)

[0043] 4. Construct long-term and short-term coupling constraints, including the following constraints: The reservoir capacity boundaries at the beginning and end of a typical day are obtained by linear interpolation of the reservoir capacity boundaries at the beginning and end of the month. The monthly available water volume of the reservoir is averaged to a typical day, and its power generation process can be used as a typical representative of that month.

[0044] (1) Relationship between the beginning and ending storage capacity of a typical day and the beginning and ending storage capacity of the month. When the number of days in that month When it is even: (41) (42) When the number of days in that month When it is an odd number: (43) (44) The initial and final reservoir capacities for a typical day are calculated using the same interpolation method.

[0045] (2) Time-based and monthly-scale flow connection (45) (46) (47)

[0046] 5. The linearization steps for nonlinear constraints in the model are as follows: To facilitate solving the model using mixed-integer linear programming (MILP) solvers such as Gurobi, it is required to linearize all nonlinear constraints. These nonlinear constraints include the relationship between reservoir surface area and capacity (17), the relationship between upstream water level and reservoir capacity (19)-(20), the relationship between tailrace water level and outflow, the constraints on the duration of unit start-up / shutdown (31)-(33), and the turbine output characteristics (24)-(25). Constraints (17), (19), and (19) are one-dimensional relationships and can be linearized through simple piecewise linear approximation. Therefore, the analysis mainly focuses on the linearization of constraints (31)-(33) and (24)-(25).

[0047] (1) Linearization of unit start / stop duration constraints It can be verified that constraints (31)-(33) can be equivalently replaced by linear constraints (48)-(50): (48) (49) (50) (2) Linearization of unit output characteristics The nonlinear characteristics of turbine generator output, i.e., the nonlinear relationship between output, head, and flow rate, can be addressed through an iterative head process. Under a fixed head, a linear fit is performed on the relationship between output and flow rate, such as... Figure 1 As shown, R² is 0.99942, indicating that there is a strong linear correlation between the two. The output of the unit can be represented by constraints (51)-(52), and the model can be transformed into a MILP problem.

[0048] (51) (52) in, and Indicates water head The slope of the fitted line; and Indicates water head The intercept of the fitted line.

[0049] Figure 2The iterative process of water head is demonstrated. The initial water head value is set as the monthly average value. Based on solving a mixed-integer linear programming model that includes constraints (51)-(52) but excludes constraints (24)-(25), the change of the target is judged. If the target is improved, the water head is updated; otherwise, the reservoir capacity is reduced. This strategy prevents the optimal solution from oscillating between two extreme values ​​and failing to converge. The water head iteration process will be repeated until the water head converges to be sufficiently close to the previous solution.

[0050] The working principle of this patent is that, given the inflow of water, the inflow is used as the input to a long-term and short-term coupled scheduling model. At the same time, the boundary conditions for the reservoir and generating units in the model are determined. After solving the scheduling model, the scheduling process of the reservoir is obtained, so that the entire scheduling process satisfies the boundary conditions and constraints of the reservoir and generating units, and maximizes the power generation benefits.

[0051] Incoming water (i.e., in formula (2)) The reservoir's water level and power generation are the main factors that determine the reservoir's scheduling process and power generation. These are generally obtained in advance through prediction methods and are therefore known inputs in the model. The boundary conditions in the model describe the constraints on the reservoir and generating units at the boundaries of the scheduling space. For the reservoir, the boundary conditions include upper and lower limits of reservoir capacity (Equations (6)-(7)) and upper and lower limits of outflow (Equations (8)-(9)). For the generating units, the boundary conditions include the duration of start / stop (Equations (48)-(50)), the number of start / stop cycles (Equation (35)), the upper and lower limits of power output (Equations (29)-(30)), and the upper and lower limits of power generation flow (Equations (27)-(28)). Once the model's inputs and boundary conditions are determined, the model can be solved using a mixed integer linear programming solver such as gurobi to obtain the reservoir's scheduling process, including the medium- and long-term scheduling process of the reservoir, i.e., the water level and power output flow of the reservoir each month, and the scheduling process of the reservoir on a typical day each month, i.e., the power output process of each generating unit in 96 time periods (15-minute intervals) per day. If the reservoir generates electricity strictly according to this scheduling process, the power generation benefits will be maximized.

[0052] To verify the superiority of the long-term and short-term coupled model considering the operating characteristics of hybrid pumped storage power stations in this patent, the Bailianhe Reservoir was selected as the research object. Three years—abundant, normal, and dry—were chosen as representative years for water inflow, and a long-term and short-term nested model was set up for comparison. The construction steps of the long-term and short-term nested model are as follows: First, simulation was performed based on the traditional medium- and long-term reservoir scheduling model to obtain the medium- and long-term reservoir scheduling process; using the medium- and long-term scheduling reservoir capacity as the boundary, the typical daily power generation process was extracted, and indicators such as power generation efficiency were calculated.

[0053] Table 1 compares the performance of the long-short coupling scheduling model and the long-short nested model. Clearly, in the three typical years, the scheduling schemes obtained by the long-short coupling model are superior to those obtained by the long-short nested model.

[0054] Table 1. Differences in benefits between long-term and short-term coupled models and long-term and short-term nested models for different typical years.

[0055] Figure 3 and Figure 4 This paper illustrates the power output of a hybrid pumped storage power station on a typical day during a high-water year under both long-term and short-term coupled models and nested long-term and short-term models. This diagram allows for in-depth analysis of the reasons for the decreased efficiency of the hybrid pumped storage power station under the nested long-term and short-term models. Because the medium- and long-term reservoir optimization scheduling model fails to fully consider the constraints of typical days, it cannot accurately reflect the intraday operating characteristics of the hybrid pumped storage power station's pumping-power generation, resulting in significant defects in the established medium- and long-term scheduling boundaries. Specifically, in February, constrained by the medium- and long-term scheduling boundaries, the allocated available water volume on typical days was too low, preventing the power station from reaching full capacity during the peak electricity price period of 9:00-15:00. In July, the allocated available water volume on typical days was too high, allowing the power station to operate at full capacity throughout the day, preventing the realization of profits through low-price pumping and high-price power generation. Therefore, the allocated available water volume on typical days should not be too low, otherwise the capacity of the high-price channel will not be fully utilized; at the same time, it should not be too high, otherwise the role of the reversible units cannot be realized. This allocation problem can be solved using a long- and short-term coupled model.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A long-term and short-term coupled scheduling method for hybrid pumped storage power stations, characterized in that, Based on existing medium- and long-term reservoir optimization scheduling models, a long- and short-term coupled scheduling model is constructed that simultaneously considers the medium- and long-term constraints and short-term operating characteristics of hybrid pumped storage power stations. By selecting a typical day each month as a representative, both the medium- and long-term monthly-scale constraints and the short-term typical day constraints of the hybrid pumped storage power station are incorporated into the model. The long- and short-term coupled scheduling model includes an objective function, medium- and long-term monthly-scale constraints, short-term typical day constraints, and long- and short-term coupled constraints. Nonlinear constraints are linearized, transforming the entire model into a mixed-integer linear programming problem, which is solved using the commercial Gurobi solver. Specific steps include: S1: Construct an objective function with the goal of maximizing power generation efficiency, introduce time-of-use pricing, and guide power plants to realize profits and peak shaving within a typical day; S2: Construct medium- and long-term monthly-scale constraints, including monthly water balance constraints, upper and lower limits of reservoir capacity constraints, and upper and lower limits of outflow constraints; S3: Construct short-term typical daily constraints, including water balance constraints between typical daily time periods, upper and lower limits constraints on reservoir capacity and outflow, constraints on the relationship between reservoir area and capacity, reservoir evaporation constraints, constraints on reservoir power generation and pumping head, constraints on the total number of generating units, constraints on unit operating status, constraints on power plant operating status, constraints on unit output characteristics, constraints on conventional unit operation restrictions, constraints on upper and lower limits constraints on unit flow and power, constraints on the duration of unit start-up / shutdown, constraints on the upper limit of the number of unit starts, constraints on reversible unit operating condition switching, constraints on the relationship between power plant output and unit output, constraints on power plant output fluctuation, constraints on channel capacity, and constraints on the relationship between time period output and power generation. S4: Construct long-term and short-term coupling constraints, including the relationship constraints between the beginning and end storage capacity of a typical day and the beginning and end storage capacity of the month, as well as the constraints on the connection between time period and monthly scale flow. S5. Linearize the nonlinear constraints in the model; S6. Given the inflow of water, use the inflow as the input to the long-term and short-term coupled scheduling model, determine the boundary conditions for the reservoir and generating units in the model, solve the model using the gurobi mixed-integer linear programming solver, and obtain the scheduling process of the reservoir.

2. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, The expression for the objective function in step S1 is: ； in, m and t These represent the month number and the time period number of a typical day, respectively. M and T These represent the total number of months and the total number of typical daily time periods, respectively. Real-time scheduling is generally done at 15-minute intervals, so we take... T =96; express m Typical intraday period of the month t Electricity price, unit: yuan / MWh; express m Typical intraday period of the month t Electricity generation, unit: MWh; for m The number of days in a month.

3. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, The specific expression for the medium- to long-term monthly scale constraint mentioned in step S2 is as follows: 2a. Monthly water balance constraint: ； ； Inbound and outbound flow satisfy: ； Upper and lower reservoir capacity boundary constraints: ； in, and For months Reservoir capacity (upper and lower reservoirs), unit: m 3 ; and For months Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months Water loss due to evaporation, unit: m 3 / s; For months Inflow to the upper reservoir, unit: m 3 / s; For months Time span, in seconds; and Given the initial and final storage capacities of the upper reservoir, typically set as the normal storage capacity, the unit is m. 3 ; The initial capacity of the given reservoir, in meters (m). 3 ; and For months Power generation flow and water discharge, unit: m³ 3 / s; 2b. Upper and lower limits of storage capacity constraints: ； in, and For months Initially, the upper and lower limits of the reservoir's capacity were given, in meters. 3 ; and For months Initial reservoir capacity limits, unit: m 3 ; 2c. Outbound flow upper and lower limit constraints: ； in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s.

4. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, The short-term typical day constraints include water balance constraints between typical day periods, upper and lower limits constraints on reservoir capacity and outflow, constraints on the relationship between reservoir area and capacity, reservoir evaporation constraints, constraints on reservoir power generation and pumping head, constraints on the total number of generating units, constraints on unit operating status, constraints on power plant operating status, constraints on unit output characteristics, constraints on conventional unit operation restrictions, constraints on upper and lower limits constraints on unit flow and power, constraints on the duration of unit start-up / shutdown, constraints on the upper limit of the number of unit starts, constraints on reversible unit operating condition switching, constraints on the relationship between power plant output and unit output, constraints on power plant output fluctuation, constraints on channel capacity, and constraints on the relationship between output and power generation during the time period.

5. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 4, characterized in that, The specific expression for the short-term typical day constraint mentioned in step S3 is as follows: (3a) Water balance constraints during typical daily periods: ； ； Inbound and outbound flow satisfy: ； in, and For months Typical day Reservoir capacity at the beginning of the period, for both the upper and lower reservoirs, in meters (m³). 3 ; and For months m Typical intraday period Outflow from the upper and lower reservoirs, in cubic meters per second (m³). 3 / s; For months m Typical intraday period Flow loss due to evaporation, unit: m 3 / s; The time span between time periods (15 minutes); For months m Typical intraday period Any unit n Power generation flow (including reversible and conventional units), unit: m³ 3 / s; For months m Typical intraday period Reversible unit Pumping flow rate, unit: m 3 / s; For months m Typical intraday period Wastewater, unit: m 3 / s; (3b) Upper and lower limits constraints on storage capacity and outbound flow: ； in, and For months m Upper and lower limits of outflow from the upper reservoir, unit: m³ 3 / s; and For months m Upper and lower limits of reservoir outflow, unit: m³ 3 / s; (3c) Constraints on the relationship between reservoir area and capacity: ； in, For months m Typical intraday period Reservoir area, unit: m 2 ; A function representing the relationship between reservoir area and reservoir capacity; (3d) Reservoir evaporation constraint: ； in, For months m Evaporation rate per unit area, expressed in m / s; (3e) Reservoir power generation and pumping head constraints: ； ； in, and Months Typical intraday period Water head during power generation and pumping, unit: m; This indicates the water level in front of the dam of the upper reservoir, determined by the reservoir capacity, in meters (m). This indicates the tailwater level determined by the outflow rate, in meters (m). This indicates the elevation of the pumping pipe installed in the lower reservoir, in meters (m). (3f) Total number of generating units constraint: ； in, , and These represent the total number of generating units, the number of conventional generating units, and the number of reversible generating units, respectively. (3g) Unit operating status constraints: ； Among them, integer variables (0 or 1) indicates the month. m Typical intraday period unit n The running status is 0, which indicates that it is not in this state, and 1 indicates that it is in this state; These represent three states: shutdown, power generation, and water pumping. (3h) Power plant operating status constraints: ； and These represent the subscripts for conventional units and reversible units, respectively. (3i) Unit output characteristic constraints; ； ； in, Indicates month m Typical intraday period unit n Power output, unit: MW; Indicates month m Typical intraday period Reversible unit Pumping power, unit: MW; Indicates the unit n The relationship between power output, head, and power generation flow rate; Indicates reversible unit The relationship between pumping power, head, and pumping flow rate; (3j) Operating constraints of conventional units: ； (3k) Unit flow and power upper and lower limit constraints: ； ； ； ； in, and Indicates the unit n Upper and lower limits of power generation flow rate, unit: m³ 3 / s; and Indicates reversible unit Upper and lower limits of pumping flow rate, unit: m³ 3 / s; and Indicates the unit n Upper and lower limits of output, unit: MW; and Indicates reversible unit Upper and lower limits of pumping power, unit: MW; (3l) Unit start / stop duration constraints: ； ； ； and satisfy: ； Among them, integer variables Indicates that the unit is Changes in state at the beginning of the period These respectively represent the unit's state from (shutdown to power generation, shutdown to pumping while maintaining the same state, power generation to shutdown, and pumping to shutdown); , and These represent the number of time periods during which the generating unit remains in at least the off, generating, or pumping states, respectively. (3m) Maximum number of unit start-ups: ； in Indicates the unit n Maximum number of startups allowed; (3n) Reversible unit operating condition switching constraints: ； (3o) Constraints on the relationship between power plant output and unit output: ； in, This indicates the total output of the power plant, in MW. Waste electricity generated by the power plant, unit: MW; (3p) Power plant output fluctuation constraints: ； in, It represents the absolute value of the output fluctuation over a period of time; This indicates the maximum allowable power output fluctuation within a given time period; (3q) Channel capacity constraint: ； in This indicates the upper limit of the transmission line channel capacity, which is generally set as the total installed capacity of the power plant; (3r) Constraints on the relationship between power output and power generation during the time period: 。 6. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, The specific expression for the long-term and short-term coupling constraints mentioned in step S4 is as follows: (4a) Constraints on the relationship between the beginning and ending storage capacity of a typical day and the beginning and ending storage capacity of that month: When the number of days in that month When it is even: ； ； When the number of days in that month When it is an odd number: ； ； The initial and final reservoir capacities on a typical day are calculated using the same interpolation method. (4b) Constraints on the connection between time period and monthly scale flow: ； ； 。 7. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, The nonlinear constraints mentioned in step S5 include constraints on the relationship between reservoir surface area and reservoir capacity, constraints on reservoir power generation and pumping head, constraints on the duration of unit start-up / shutdown, and constraints on unit output characteristics. The constraints on the relationship between reservoir surface area and reservoir capacity, and the constraints on reservoir power generation and pumping head are linearized through piecewise linear approximation. The linearization methods for the constraints on the duration of unit start-up / shutdown and the constraints on unit output characteristics are as follows: (5a) Linearization of unit start / stop duration constraints: The unit start / stop duration constraint is equivalently replaced with a linear constraint: ； ； ； (5b) Linearization of unit output characteristic constraints: The nonlinear problem of turbine unit output characteristics is addressed through an iterative head process. Under a fixed head, a linear fit is performed on the relationship between output and flow rate to obtain linear constraints. ； ； in, and Indicates water head The slope of the fitted line; and Indicates water head The intercept of the fitted line.

8. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 7, characterized in that, The head iteration process is as follows: the initial head value is set to the monthly average value, a mixed integer linear programming model is solved that includes linear constraints on the unit output characteristics but excludes nonlinear constraints on the unit output characteristics, the change of the target is judged, if the target is improved, the head is updated, otherwise the reservoir capacity range is reduced, and the above process is repeated until the head converges to be sufficiently close to the previous solution.

9. The long-term and short-term coupled dispatching method for hybrid pumped storage power stations as described in claim 1, characterized in that, In step S6, the inflow of water to the upper reservoir is included in the monthly water balance constraint; the upper and lower limits of reservoir capacity are included in the upper and lower limits of reservoir capacity constraint; the upper and lower limits of outflow are included in the upper and lower limits of outflow; the unit state holding time parameter is included in the linear constraint of unit start / stop duration; and the maximum number of unit starts is included in the upper limit constraint of unit start times. The boundary conditions include the upper and lower limits of output and the upper and lower limits of power generation flow in the constraints of unit flow and power.

10. The long-term and short-term coupled scheduling method for hybrid pumped storage power stations as described in claim 1, characterized in that, The reservoir scheduling process in step S6 includes the long-term scheduling process and the scheduling process of the reservoir on typical days each month; the long-term scheduling process of the reservoir is the water level and output flow of the reservoir each month; the scheduling process of the reservoir on typical days each month is the output process of each unit in 96 time periods within a day.

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