Economic operation scheduling method and system of water source pump station based on time-of-use electricity price

Abstract

This invention provides a method and system for economical operation scheduling of water source pumping stations based on time-of-use pricing. By constructing a two-layer architecture model for water lifting capacity configuration and start-up combination decision-making, and using unit start-up and shutdown limits, canal system safety operation, and ten-day water lifting targets as constraints, an optimization model is built and solved to minimize pumping station operating energy consumption and electricity costs, accurately generating start-up combination schemes for each time period within a ten-day period. This invention overcomes the scheduling limitations of discrete flow regulation for constant-speed pump units, comprehensively considering engineering safety, water supply safety, and operational economy. It constructs a scheduling methodology adapted to the dual constraints of poor unit flexibility and weak canal system regulation and storage, achieving economical operation based on time-of-use pricing while ensuring the dynamic optimization performance of the model, improving the robustness and intelligence of scheduling decisions, and filling the research gap in the optimized scheduling of pure constant-speed pump water source pumping stations.

Description

Technical Field

[0001] This invention belongs to the field of energy management technology and relates to a method and system for the economical operation and scheduling of water source pumping stations. Background Technology

[0002] In long-distance water diversion projects, when the water source pumping station regulates flow solely by starting and stopping fixed-speed pumps, the water intake flow exhibits significant abrupt changes, making it difficult to match the stable water demand of users along the route. This mismatch is particularly problematic when the main water conveyance canal has limited storage capacity and lacks an online storage reservoir. Such mismatch can easily lead to water levels exceeding limits in the canal system (e.g., insufficient tunnel clearance or overflowing open channels), seriously threatening project safety. To ensure operational safety, the actual scheduling of water source pumping stations often necessitates conservative and feasible solutions, resulting in high energy costs for pumping and a failure to effectively utilize economic adjustment mechanisms such as time-of-use pricing.

[0003] The current scheduling methods for water source pumping stations mainly suffer from the following key problems: 1. Severely limited scheduling flexibility: Existing research mostly focuses on pumping stations equipped with adjustable pump sets (variable speed / variable diameter / variable angle) or combinations of large and small pumps, whose flow can be continuously or finely adjusted. For pumping stations that are only equipped with non-adjustable fixed-speed pump sets in reality, their flow output is discrete and varies in large steps, and related optimization scheduling research is seriously insufficient. 2. Insufficient overall safety considerations: Most existing studies only focus on the operational economy of the pumping station itself (such as the lowest energy consumption per station), which is a local optimization and fails to systematically couple and optimize it with the overall project safety and water supply safety. 3. Lack of optimization scheduling methodology: Under the dual rigid constraints of poor unit adjustment flexibility and weak canal storage capacity, the industry still lacks an intelligent optimization scheduling methodology that can coordinate safety, water supply and economic goals. 4. Low level of intelligent decision-making: There is a lack of intelligent decision-making tools that can automatically generate ten-day (or medium-to-long-term) start-up combination schemes and can utilize time-of-use electricity pricing policies to achieve economic operation, making it difficult to achieve the goal of improving quality and efficiency. Summary of the Invention

[0004] To address the problems of severely limited scheduling flexibility, insufficient safety coordination, lack of optimized scheduling methodology, and low level of intelligent decision-making in water source pumping stations as described in the background art, this invention provides a method and system for economical operation scheduling of water source pumping stations based on time-of-use pricing.

[0005] In a first aspect, the present invention provides a method for economical operation scheduling of water source pumping stations based on time-of-use pricing, comprising: Based on the preliminary design report of the water source pumping station, obtain the design data of the water source pumping station and the safe operation conditions of the main water conveyance canal; Based on the time-of-use electricity pricing policy of the area where the water source pumping station is located, high and low electricity price periods are divided. Based on the past operating data and operation plan of the water source pumping station, obtain the water lifting volume deviation and ten-day water volume scheduling plan of the water source pumping station in the previous ten-day period; An economic operation model for water source pumping stations based on time-of-use pricing is constructed. This model adopts a two-layer architecture, including a water pumping volume allocation layer and a start-up combination decision layer. The water pumping volume allocation layer determines the ten-day water pumping volume target based on the previous ten-day water pumping volume deviation and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the pumping station's energy consumption and electricity costs, using the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target as constraints. Solve the objective function of the economic operation model of the water source pumping station to obtain the start-up combination scheme of the water source pumping station for each time period of each day within a ten-day period; The water source pumping stations are scheduled for economical operation based on the daily operating combination plan for each time period within a ten-day period.

[0006] Furthermore, the design data of the water source pumping station includes the number of pump units equipped in the pumping station, the prototype energy characteristic curve of the pump, the layout of the pumping station's inlet and outlet water systems, and the calculation results of the hydraulic losses of the inlet and outlet water systems. Based on the prototype energy characteristic curve of the water pump, the flow-head curve and flow-efficiency curve of a single water pump are obtained by fitting; based on the hydraulic loss calculation results of the inlet and outlet water system, the pipeline characteristic curve of the pump station inlet and outlet water system is obtained by fitting. The safe operation conditions of the main water conveyance canal include the upper and lower limits of the water storage capacity of the main water conveyance canal, and the limit on the single jump amplitude when adjusting the number of pumps started at the water source pumping station. The upper and lower limits of the water storage capacity of the main water conveyance canal are determined based on the preliminary design report of the water source pumping station, and the limit on the single jump amplitude of the number of pumps started is determined based on the safety of the non-steady flow transition process of the main water conveyance canal under the step flow boundary and the operation and management requirements of the pumping station.

[0007] Furthermore, based on the prototype energy characteristic curve of the water pump, the performance curve of a single water pump is fitted, namely the flow-head curve shown in equation (1) and the flow-efficiency curve shown in equation (2); based on the hydraulic loss calculation results of the inlet and outlet water system, the pipeline characteristic curve of the pump station inlet and outlet water system is fitted, as shown in equation (3), and the expression is as follows: (1), (2), (3), Where A1, A2, A3 and B1, B2, B3 are fitting coefficients, and Q is the water pump flow rate; For single-pump water lifting head; This refers to the single-pump water lifting efficiency; The water inlet and outlet systems require a head; The difference in water levels between the inlet and outlet pools of the pumping station. , The water level in the inlet pool. This refers to the water level in the outlet pool. The hydraulic losses in the inlet and outlet water system pipelines are expressed as... S is the resistance coefficient of the pipeline system.

[0008] Furthermore, the process of constructing the economic operation model of the water source pumping station includes: Based on the division of high and low electricity price periods, the number of pumping stations in operation during each high and low electricity price period remains unchanged. The number of pumping stations in operation during each high and low electricity price period, X(i), is the decision variable, where i is the period number. The economic operation model of the water source pumping station makes a decision on the daily operation combination scheme of the water source pumping station for each of the next two ten-day periods (20 days). Each day is divided into k high and low electricity price periods, and the total number of decision variables is 20k, i.e., i=1-20k. The objective function for minimizing the energy consumption and electricity cost of pump station operation is shown in equation (4): (4), In the formula, i is the time period number, 1≤i≤20k; X(i) is the number of pumping stations in operation during the i-th time period; P(i) is the single pumping power during the i-th time period; E(i) is the average electricity price during the i-th time period; T s (i) represents the length of the i-th time period; The calculation of the single pump lifting power P(i) needs to consider the impact of the number of pumps in parallel on the pumping flow, efficiency and power of the pumping station. It is obtained by combining the pumping head, pumping flow and operating efficiency of the pumping station after multiple pumps are connected in parallel with the density of water, gravitational acceleration and motor efficiency.

[0009] Furthermore, the calculation formula for the single pump water lifting power P(i) is shown in equations (5)-(7): (5), (6), (7), In the formula, H pumpstation The pumping head of a pumping station with multiple pumps connected in parallel; Q pumpstation η is the water flow rate of a pumping station after multiple pumps are connected in parallel. pumpstation ρ is the pumping station efficiency after multiple pumps are connected in parallel; g is the density of water; η0 is the acceleration due to gravity; and η0 is the efficiency of the electric motor.

[0010] Furthermore, the upper and lower limits on the number of pump units in operation are used to limit the number of units in operation and reduce the frequency of pump station start-up and shutdown, specifically as follows: The number of pumps operating at any given time period must not exceed the maximum limit. (8), In the formula, N max This refers to the maximum number of pumps allowed to be operated during normal operation of the water source pumping station. The number of pumping units operating during the high electricity price period at the beginning of the ten-day period should be equal to the number operating during the high electricity price period at the end of the previous ten-day period, thereby reducing the frequency of pumping station unit start-ups and shutdowns. (9), In the formula, X(1) represents the number of generating units started during the period of high electricity prices at the beginning of the ten-day period; X last This refers to the number of pump stations that were in operation during the period of high electricity prices at the end of the previous ten-day period; The number of pumping units operating during the peak electricity price period at the end of each day within a ten-day period should be equal to the number operating during the peak electricity price period at the beginning of the following day, thereby reducing the frequency of pump station start-ups and shutdowns. (10) In the formula, n is the number of days in the decision domain, n = 1 - 19; The aforementioned engineering safety constraints are used to consider the single jump amplitude of the number of pump stations in operation and the storage capacity limit of the main water conveyance canal, to ensure the water level safety during the operation of the main water conveyance canal, specifically: Limit the single jump in the number of pumps started at a water source pumping station: (11), In the formula, Limits the single jump in the number of pump stations in operation; To ensure the safety of the main water conveyance canal's water level, the canal's storage capacity must fluctuate within the allowable storage range at all times. (12), In the formula, Let be the storage capacity of the main water conveyance canal during the i-th time period; This is the lower limit of the water storage capacity; This is the upper limit of the water storage capacity; Water storage capacity of the main water conveyance canal at different times The calculation method is as follows: (13) In the formula, This represents the initial storage capacity of the main water conveyance canal at the beginning of the ten-day period; Let the total water distribution flow along the main water conveyance canal during the i-th time period be denoted as . The ten-day water extraction target constraint is used to respond to the engineering ten-day water extraction scheduling plan and reduce the deviation of the ten-day water extraction volume, specifically as follows: The water pumping volume of pumping stations within the decision-making area per ten-day period should be within the allowable deviation range of the ten-day target water pumping volume: (14) (15) In the formula, Let be the water pumping flow rate of the water source pumping station in the i-th time period; The water extraction target for the first ten days within the decision domain is given by the water extraction allocation layer; The target water extraction volume for the second ten-day period within the decision domain is set solely based on the ten-day water volume scheduling plan and is provided by the water extraction volume allocation layer; α represents the allowable deviation of the ten-day water extraction volume. The water pumping target for the first ten-day period is the sum of the average water pumping target value for the first ten-day period and the deviation of the water pumping volume from the previous ten-day period. The average water pumping target value for the first ten-day period is the average water pumping volume value for the ten-day period. The total monthly water pumping target for the water source pumping station is obtained based on the monthly water volume scheduling plan for each month. The total monthly water pumping target is then evenly distributed to each ten-day period to obtain the average water pumping target for each ten-day period.

[0011] Furthermore, a genetic algorithm is used to solve the objective function of the economic operation model of the water source pumping station to obtain integer solutions, thereby obtaining the daily operating combination scheme of the water source pumping station for each time period within a ten-day period; In the economic operation scheduling of water source pumping stations, a rolling optimization strategy is adopted. Each time the economic operation model of the water source pumping station is called, the start-up combination scheme for the next two weeks is decided, but only the decision scheme for the first week is output and executed; the above optimization solution process is repeated at the beginning of the next week.

[0012] Secondly, the present invention provides an economic operation scheduling system for water source pumping stations based on time-of-use electricity pricing, including a module for obtaining water source pumping station design data and safe operation conditions of the main water conveyance canal, a module for dividing high and low electricity price periods, a module for obtaining water pumping volume deviation and ten-day water volume scheduling plan, a module for constructing an economic operation model of water source pumping stations, a module for solving the economic operation model, and an economic operation scheduling module. The module for obtaining design data of water source pumping stations and safe operation conditions of main water conveyance canals acquires design data of water source pumping stations and safe operation conditions of main water conveyance canals based on the preliminary design report of the water source pumping station. The high and low electricity price time period division module divides the high and low electricity price time periods according to the time-of-use electricity price policy of the area where the water source pumping station is located; The module for obtaining the water pumping deviation and ten-day water volume scheduling plan obtains the water pumping deviation and ten-day water volume scheduling plan of the water source pumping station in the previous ten-day period based on the past operating data and operating plan of the water source pumping station. The water source pumping station economic operation model construction module constructs an economic operation model for water source pumping stations based on time-of-use electricity pricing. This model adopts a two-layer architecture, including a water pumping volume configuration layer and a start-up combination decision layer. The water pumping volume configuration layer determines the ten-day water pumping volume target based on the previous ten-day water pumping station's pumping volume deviation and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station's design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the pumping station's operating energy consumption and electricity costs, using the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target as constraints. The economic operation model solving module solves the objective function of the economic operation model of the water source pumping station to obtain the start-up combination scheme of the water source pumping station for each time period of each day within a ten-day period. The economic operation scheduling module performs economic operation scheduling of water source pumping stations based on the daily operating combination scheme of water source pumping stations within a ten-day period.

[0013] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to realize the above-described method for economical operation scheduling of water source pumping stations based on time-of-use pricing.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described method for economical operation scheduling of water source pumping stations based on time-of-use pricing.

[0015] Compared with the prior art, the present invention has the following advantages: (1) High flexibility of operation and control: Existing scheduling technologies are mostly adapted to adjustable pump sets or combinations of large and small pumps. For pump stations equipped only with non-adjustable fixed-speed pump sets, the flow regulation is discrete and the step span is large, resulting in a serious lack of scheduling flexibility. This invention focuses on such actual engineering scenarios, relies on the economic operation model of the two-layer architecture, and combines the pump station design data and the time-of-use electricity price time period division results to carry out optimization decisions. It breaks the rigid constraint of the flow regulation of fixed-speed pump sets, solves the pain point of large step changes in water intake flow under the traditional scheduling mode and difficulty in adapting to the stable water distribution demand, and makes the scheduling and control of fixed-speed pump water source pump stations more adaptable, filling the gap in the research on the optimization scheduling of such pump stations. (2) Achieving synergistic optimization of safety and economy: Existing scheduling studies mostly focus on the energy consumption economy of a single pump station, which is a local optimization and does not couple with core constraints such as engineering safety and water supply safety, which can easily lead to problems such as water level exceeding the limit in the canal system and high risks in engineering operation. This invention incorporates the limit on the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the target water volume per ten days into the model constraints, and coordinates the multi-dimensional constraints. It systematically couples and optimizes the economic goal of pump station operation with the overall safety and water supply guarantee needs of the water conveyance project. This avoids safety hazards such as insufficient canal clearance and overflow of open channels, and also abandons the conservative scheduling mode, achieving multi-objective synergy of engineering safety, water supply safety and operation economy, and completely changing the inherent drawbacks of local optimization. (3) Adapting to dual rigid constraints: Under the dual rigid constraints of poor unit adjustment flexibility and weak canal storage capacity, the industry has long lacked a mature overall optimization scheduling methodology, resulting in no scientific guidance for the scheduling of water source pumping stations. This invention innovatively builds a two-layer architecture model of water lifting volume configuration layer and start-up combination decision layer, forming a complete optimization scheduling methodology adapted to this special operating scenario. Based on the water lifting volume deviation of the previous ten-day period and the ten-day water volume scheduling plan, the ten-day water lifting volume target is accurately determined. Then, the start-up combination optimization is carried out in combination with time-of-use electricity price, providing a standardized and feasible technical solution for the scheduling work of similar water source pumping stations, and solving the industry problem of scheduling without a solution under dual constraints. (4) Reduce operating electricity costs and improve the intelligence level of dispatching: Traditional dispatching mode lacks intelligent decision-making tools and cannot rely on time-of-use pricing policies to optimize dispatching. It can only rely on manual formulation of conservative plans, resulting in high energy consumption and low decision-making efficiency. This invention constructs and solves a function with the goal of minimizing the energy consumption and electricity costs of pumping station operation, automatically generating a ten-day start-up combination plan, making full use of time-of-use pricing policies to achieve peak-shifting optimization dispatching, and significantly reducing the electricity cost of pumping stations for water lifting. At the same time, it realizes the intelligent generation of dispatching plans, gets rid of the limitations of manual decision-making, and effectively improves the intelligence level of water source pumping station dispatching. (5) Stable and reliable scheduling decision: The two-layer architecture economic operation model designed in this invention has dynamic optimization characteristics. During the scheduling optimization process, it can take into account the regulation and storage capacity of the main water conveyance canal, prevent excessive consumption of water storage in the canal system, and avoid subsequent operation risks caused by water storage imbalance. At the same time, relying on the dynamic optimization logic, it ensures the rationality and robustness of the decision result of the number of pumps to be started at the end of the ten-day period, and prevents the scheduling scheme from becoming extreme or unreasonable. It ensures that the operation and scheduling of pump stations throughout the ten-day period remains stable and controllable, and improves the practicality and long-term effectiveness of the scheduling scheme.

[0016] In summary, this invention constructs a two-layer architecture model for water lifting capacity configuration and start-up combination decision-making. Constrained by unit start-up and shutdown limits, canal system safety operation, and ten-day water lifting capacity targets, it builds and solves an optimization model aimed at minimizing pump station operating energy consumption and electricity costs, accurately generating start-up combination schemes for each time period within a ten-day period. This invention overcomes the scheduling limitations of discrete flow regulation for constant-speed pump units, comprehensively considering engineering safety, water supply safety, and operational economy. It constructs a scheduling methodology adapted to the dual constraints of poor unit flexibility and weak canal system regulation and storage, achieving economical operation based on time-of-use pricing while ensuring the dynamic optimization performance of the model. This improves the robustness and intelligence of scheduling decisions, filling the research gap in the optimal scheduling of pure constant-speed pump water source pumping stations. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention.

[0018] Figure 2 This is a two-layer architecture for the economic operation model of a water source pumping station in Embodiment 1 of the present invention.

[0019] Figure 3 This is a system architecture diagram of Embodiment 2 of the present invention.

[0020] Figure 4 The results are the optimized test conditions for Example 5 of this invention.

[0021] Figure 5 The results are the mid-term optimization results of the test conditions in Embodiment 5 of the present invention.

[0022] Figure 6 The results are optimized for the test conditions in Example 5 of this invention. Detailed Implementation

[0023] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0024] Example 1 The flowchart of the economic operation and scheduling method for water source pumping stations based on time-of-use pricing is as follows: Figure 1 As shown, the specific steps are as follows.

[0025] Based on the preliminary design report of the water source pumping station, obtain the design data of the water source pumping station and the safe operation conditions of the main water conveyance canal.

[0026] Specifically, the design data for water source pumping stations includes the number of pump units equipped in the pumping station, the prototype energy characteristic curves of the pumps, the layout of the pumping station's inlet and outlet water systems, and the calculation results of the hydraulic losses of the inlet and outlet water systems.

[0027] More specifically, based on the prototype energy characteristic curve of the water pump, the performance curve of a single water pump is fitted, namely the flow-head curve shown in equation (1) and the flow-efficiency curve shown in equation (2); based on the hydraulic loss calculation results of the inlet and outlet water system, the pipeline characteristic curve of the pump station inlet and outlet water system is fitted, as shown in equation (3), and the expression is as follows: (1), (2), (3), Where A1, A2, A3 and B1, B2, B3 are fitting coefficients, and Q is the water pump flow rate; For single-pump water lifting head; This refers to the single-pump water lifting efficiency; The water inlet and outlet systems require a head; The difference in water levels between the inlet and outlet pools of the pumping station. , The water level in the inlet pool. This refers to the water level in the outlet pool. The hydraulic losses in the inlet and outlet water system pipelines are expressed as... S is the resistance coefficient of the pipeline system.

[0028] Specifically, the safe operation conditions of the main water conveyance canal include the upper limit of the main water conveyance canal's water storage capacity. and lower limit of water storage capacity Limitation of single jump amplitude when adjusting the number of pumps started at a water source pumping station The upper and lower limits of the water storage capacity of the main water conveyance canal are determined based on the preliminary design report of the water source pumping station. The limit on the single jump amplitude of the number of pumps in operation is determined based on the safety requirements of the non-steady flow transition process of the main water conveyance canal under the step flow boundary and the operation and management requirements of the pumping station. Specifically, the limit on the single jump amplitude when adjusting the number of pumps in operation at the water source pumping station is... The value of is not the focus of this invention, and therefore is not within the scope of this discussion. The initial water storage capacity of the main water conveyance canal at the beginning of the ten-day period is used as an input parameter for the economic operation model of the water source pumping station. It can be estimated by the engineering management unit based on the relationship curve of water conveyance flow rate, water level in front of the gate, and water storage capacity of each canal section, or calculated using a hydrodynamic simulation model. The value of the initial water storage capacity of the main water conveyance canal at the beginning of the ten-day period is not the focus of this invention, and therefore is not within the scope of this discussion.

[0029] Based on the time-of-use electricity pricing policy of the area where the water source pumping station is located, high and low electricity price periods are divided.

[0030] Specifically, based on the regional time-of-use pricing policy, the 24-hour peak, flat, and valley electricity price periods are further integrated into a high-price period at the beginning of the day, a low-price period in the middle of the day, and a high-price period at the end of the day. The electricity price for each period is the average of the hourly prices within that period. The starting point of the high-price period at the beginning of the day is the time at which the economic operation model of the water source pumping station is invoked at the beginning of each ten-day period, which is determined by the project management unit.

[0031] Based on past operating data and operational plans of the water source pumping stations, the deviation in water pumping volume and the ten-day water volume scheduling plan of the previous ten-day period are obtained.

[0032] Specifically, at the beginning of each ten-day period, the latest ten-day water allocation plan is obtained, and based on historical water extraction records, the water extraction deviation of the previous ten-day water source pumping station is calculated to formulate the ten-day water extraction target.

[0033] An economic operation model for water source pumping stations based on time-of-use electricity pricing is constructed. This model employs a two-layer architecture, comprising a water pumping volume allocation layer and a start-up combination decision layer. The water pumping volume allocation layer determines the ten-day water pumping volume target based on the previous ten-day water pumping volume deviation and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the pumping station's energy consumption and electricity costs, constrained by the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target.

[0034] Specifically, the two-tier architecture of the economic operation model for water source pumping stations is as follows: Figure 2 As shown, the process of constructing the economic operation model of a water source pumping station includes: Based on the division of high and low electricity price periods, the number of pumping stations in operation during each high and low electricity price period remains unchanged. The number of pumping stations in operation during each high and low electricity price period, X(i), is the decision variable, where i is the period number. The economic operation model of the water source pumping station makes a decision on the daily operation combination scheme of the water source pumping station for each of the next two ten-day periods (20 days). Each day is divided into k high and low electricity price periods, and the total number of decision variables is 20k, i.e., i=1-20k. The objective function for minimizing the energy consumption and electricity cost of pump station operation is shown in equation (4): (4), In the formula, i is the time period number, 1≤i≤20k; X(i) is the number of pumping stations in operation during the i-th time period; P(i) is the single pumping power during the i-th time period; E(i) is the average electricity price during the i-th time period; T s (i) represents the length of the i-th time period; The calculation of the single-pump water lifting power P(i) needs to consider the influence of the number of pumps connected in parallel on the pumping station's water flow rate, efficiency, and power. It is obtained by combining the pumping head, water flow rate, and operating efficiency of the pumping station after multiple pumps are connected in parallel with the density of water, gravitational acceleration, and motor efficiency. The calculation formulas for the single-pump water lifting power P(i) are shown in equations (5)-(7): (5), (6), (7), In the formula, H pumpstation The pumping head of a pumping station with multiple pumps connected in parallel; Q pumpstation η is the water flow rate of a pumping station after multiple pumps are connected in parallel. pumpstation ρ is the pumping station efficiency after multiple pumps are connected in parallel; g is the density of water; η0 is the acceleration due to gravity; and η0 is the efficiency of the electric motor.

[0035] Specifically, the upper and lower limits on the number of pump units in operation are used to limit the number of units in operation and reduce the frequency of pump station start-up and shutdown. The number of pumps operating at any given time period must not exceed the maximum limit. (8), In the formula, N max This refers to the maximum number of pumps allowed to be operated during normal operation of the water source pumping station. The number of pumping units operating during the high electricity price period at the beginning of the ten-day period should be equal to the number operating during the high electricity price period at the end of the previous ten-day period, thereby reducing the frequency of pumping station unit start-ups and shutdowns. (9), In the formula, X(1) represents the number of generating units started during the period of high electricity prices at the beginning of the ten-day period; X last This refers to the number of pump stations that were in operation during the period of high electricity prices at the end of the previous ten-day period; The number of pumping units operating during the peak electricity price period at the end of each day within a ten-day period should be equal to the number operating during the peak electricity price period at the beginning of the following day, thereby reducing the frequency of pump station start-ups and shutdowns. (10) In the formula, n is the number of days in the decision domain, n = 1 - 19; The aforementioned engineering safety constraints are used to consider the single jump amplitude of the number of pump stations in operation and the storage capacity limit of the main water conveyance canal, to ensure the water level safety during the operation of the main water conveyance canal, specifically: Limit the single jump in the number of pumps started at a water source pumping station: (11), In the formula, Limits the single jump in the number of pump stations in operation; To ensure the safety of the main water conveyance canal's water level, the canal's storage capacity must fluctuate within the allowable storage range at all times. (12), In the formula, Let be the storage capacity of the main water conveyance canal during the i-th time period; This is the lower limit of the water storage capacity; This is the upper limit of the water storage capacity; Water storage capacity of the main water conveyance canal at different times The calculation method is as follows: (13) In the formula, This represents the initial storage capacity of the main water conveyance canal at the beginning of the ten-day period; Let the total water distribution flow along the main water conveyance canal during the i-th time period be denoted as . The ten-day water extraction target constraint is used to respond to the engineering ten-day water extraction scheduling plan and reduce the deviation of the ten-day water extraction volume, specifically as follows: The water pumping volume of pumping stations within the decision-making area per ten-day period should be within the allowable deviation range of the ten-day target water pumping volume: (14) (15) In the formula, Let be the water pumping flow rate of the water source pumping station in the i-th time period; The water extraction target for the first ten days within the decision domain is given by the water extraction allocation layer; The target water extraction volume for the second ten-day period within the decision domain is set solely based on the ten-day water volume scheduling plan and is provided by the water extraction volume allocation layer; α represents the allowable deviation of the ten-day water extraction volume. The water pumping target for the first ten-day period is the sum of the average water pumping target value for the first ten-day period and the deviation of the water pumping volume from the previous ten-day period. The average water pumping target value for the first ten-day period is the average water pumping volume value for the ten-day period. The total monthly water pumping target for the water source pumping station is obtained based on the monthly water volume scheduling plan for each month. The total monthly water pumping target is then evenly distributed to each ten-day period to obtain the average water pumping target for each ten-day period.

[0036] This is because external disturbances and uncertainties exist during the pumping process, leading to deviations in the pumping volume. To ensure the accurate implementation of the monthly water allocation plan, the target value for the first ten-day period is determined as the sum of the average ten-day pumping volume target value and the deviation from the previous ten-day period; the target value for the second ten-day period is the average ten-day pumping volume value.

[0037] The objective function of the economic operation model of the water source pumping station is solved to obtain the daily operating combination scheme of the water source pumping station for each time period within a ten-day period.

[0038] Specifically, a genetic algorithm is used to solve the objective function of the economic operation model of the water source pumping station to obtain integer solutions, thereby obtaining the daily operating combination scheme of the water source pumping station for each time period within a ten-day period.

[0039] Solving the objective function is essentially solving a single-objective, multi-constraint, nonlinear, integer programming problem. This invention employs a genetic algorithm for optimization, utilizing the `ga` function in computer software. The `ga` (Genetic Algorithm) function is a genetic algorithm tool used to solve global optimization problems, effectively handling complex search spaces and exploring integer solutions in parallel under various constraints. In practice, algorithm parameters such as population size, maximum number of iterations, and stopping generation need to be adjusted; other parameters use the default algorithm values.

[0040] The water source pumping stations are scheduled for economical operation based on the daily operating combination plan for each time period within a ten-day period.

[0041] In practice, if only the combination of pumping units operating within a ten-day period is considered, the decision domain is typically set to one ten-day period. However, for water source pumping stations with limited unit control flexibility and weak downstream main water conveyance canal storage capacity, the economic operation model may, in order to reduce pump operation and lower energy consumption and electricity costs, fully utilize the main water conveyance canal's storage capacity to continuously supply water to users. This may result in excessively low canal storage at the end of the ten-day period, making it difficult to find a feasible solution when the model is called again in the next ten-day period.

[0042] Therefore, a rolling optimization strategy is adopted in the economic operation scheduling of water source pumping stations. Each time the economic operation model of the water source pumping station is called, the start-up combination scheme for the next two ten-day periods is decided, but only the decision scheme for the first ten-day period is output and executed. The above optimization solution process is repeated at the beginning of the next ten-day period, thereby effectively avoiding the problem of low channel storage at the end of the ten-day period. The rolling optimization strategy enables the economic operation model of the water source pumping station to have dynamic optimization performance, which can ensure the rationality and robustness of the decision result of the number of pumps to be started at the end of the ten-day period while preventing excessive consumption of water storage in the main water conveyance canal.

[0043] Specifically, at the beginning of each ten-day period, data such as the water storage volume of the main water conveyance canal, the ten-day water allocation plan, the water extraction deviation of the previous ten-day period, and the number of pumping stations in operation at the end of the previous ten-day period are obtained. These data serve as input parameters for the economic operation model of the water source pumping stations. After model optimization and solution, the optimized decision-making results of the daily operation combination scheme for each time period of the ten-day period are output, guiding the start-up and shutdown process of the water source pumping stations within the ten-day period. The above solution process is repeated at the beginning of the next ten-day period.

[0044] Example 2 The architecture diagram of the water source pumping station economic operation scheduling system based on time-of-use pricing is as follows: Figure 3As shown, it consists of a module for obtaining design data of water source pumping stations and safe operation conditions of the main water conveyance canal, a module for dividing high and low electricity price periods, a module for obtaining water pumping volume deviation and ten-day water volume scheduling plan, a module for constructing an economic operation model of water source pumping stations, a module for solving the economic operation model, and a module for economic operation scheduling.

[0045] The module for obtaining design data of water source pumping stations and safe operation conditions of main water conveyance canals is based on the preliminary design report of the water source pumping station.

[0046] The module for dividing high and low electricity price periods determines the high and low electricity price periods based on the time-of-use electricity pricing policy of the area where the water source pumping station is located.

[0047] The module for obtaining water pumping deviation and ten-day water volume scheduling plan obtains the water pumping deviation and ten-day water volume scheduling plan of the water source pumping station in the previous ten-day period based on the past operation data and operation plan of the water source pumping station.

[0048] The module for constructing an economic operation model for water source pumping stations builds an economic operation model for water source pumping stations based on time-of-use electricity pricing. This model adopts a two-layer architecture, including a water pumping volume configuration layer and a start-up combination decision layer. The water pumping volume configuration layer determines the ten-day water pumping volume target based on the water pumping volume deviation of the previous ten-day period and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the energy consumption and electricity costs of pumping station operation, using the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target as constraints.

[0049] The economic operation model solving module solves the objective function of the economic operation model of the water source pumping station and obtains the start-up combination scheme of the water source pumping station for each time period of each day within a ten-day period.

[0050] The economic operation scheduling module performs economic operation scheduling of water source pumping stations based on the daily operating combination plan for each time period within a ten-day period.

[0051] The specific implementation methods of each module in this system are the same as those described in Example 1, and will not be repeated here.

[0052] Example 3 An electronic device includes a memory and a processor, the memory and the processor being communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to implement the time-of-use pricing-based economic operation scheduling method for water source pumping stations as described in Embodiment 1 above, and the time-of-use pricing-based economic operation scheduling system for water source pumping stations as described in Embodiment 2.

[0053] Example 4 A computer-readable storage medium storing a computer program that, when executed by a processor, implements the time-of-use pricing-based economic operation scheduling method for water source pumping stations as described in Embodiment 1 above, and the time-of-use pricing-based economic operation scheduling system for water source pumping stations as described in Embodiment 2.

[0054] Example 5 Step 1: Obtain design data for a water source pumping station and the safe operating conditions of the main water conveyance canal. According to the preliminary design report of a certain water diversion project, a certain water source pumping station is equipped with 12 units of the same model of large flow, high head, constant speed pumps, of which 10 are in use and 2 are on standby. The water flow regulation is achieved solely by starting and stopping the pumps. Based on the prototype energy characteristic curve of the pumps and the hydraulic loss calculation results of the pumping station's inlet and outlet water system, the flow-head curve and flow-efficiency curve of a single pump are obtained as shown in equations (16) and (17), and the pipeline characteristic curve of the pumping station's inlet and outlet water system is shown in equation (18). Within the operating flow range, the operating efficiency of the pumping station's units remains basically unchanged, approximately 93%, as shown in equations (16)-(18) below: (16), (17), (18), In the formula, Q is the water pump flow rate, m 3 / s;H pump For a single pump, the head is measured in meters (m); η pump For single-pump water lifting efficiency; H r The required head (m) for the inlet and outlet water systems; Z 进水池 The water level in the inlet pool is in meters (m).

[0055] Considering the long length of the main water conveyance canal (approximately 665 km), it takes a considerable amount of time for flow changes at the head pumping stations to be transmitted to the end of the main canal. To avoid frequent operation of the sluice gates along the route during operation and scheduling, only the storage capacity of the first two canal sections (approximately 117 km in length) will be used to regulate the difference in water extraction volume during periods of high and low electricity prices at the pumping stations. According to the preliminary design report of a certain water diversion project, the upper limit of the storage capacity of the first two canal sections is: Storage max 6.013 million m 3 Lower limit of water storage capacity min 3.599 million m 3 The storage capacity is approximately 2.414 million m³. 3 .

[0056] Taking into account the safety of the non-steady flow transition process of the main water conveyance canal under the step flow boundary and the operation and management requirements of the pumping station, the single jump amplitude limit N when adjusting the number of pumping stations in operation is set. safe Four units would be appropriate.

[0057] The second step is to obtain the regional time-of-use electricity pricing policy and divide the high and low electricity price periods. Table 1 shows an overview of the time-of-use electricity pricing policy in the province where a certain water source pumping station is located. A day is divided into peak, normal, and off-peak periods, with significant price fluctuations throughout the day, indicating substantial room for cost optimization in the pumping station's operation. Based on the recommended electricity price adopted in the preliminary design report of a certain water diversion project, the base price is set at 0.3623 yuan / kWh.

[0058] Table 1. Overview of Time-of-Use Electricity Pricing Policies in the Province Where a Certain Water Source Pumping Station is Located Assuming the model is invoked before 9:00 AM at the beginning of each ten-day period, the next 24 hours are divided into three time periods according to the time-of-use pricing policy: 9:00 AM to 11:00 PM is the high-price period at the beginning of the day, with an average price of 0.4658 yuan / kWh; 11:00 PM to 7:00 AM is the low-price period in the middle of the day, with an average price of 0.1812 yuan / kWh; and 7:00 AM to 9:00 AM is the high-price period at the end of the day, with an average price of 0.3623 yuan / kWh.

[0059] The third step is to obtain the initial water storage volume of the main water conveyance canal at the beginning of the ten-day period, the water allocation plan for the ten-day period, and the deviation of the water lifting volume from the previous ten-day period. A hydrodynamic simulation model was used to calculate the water storage capacity of the main water conveyance canal at the beginning of each ten-day period, which served as the input parameter for the economic operation model of the water source pumping station. At the beginning of each ten-day period, the latest ten-day water volume scheduling plan was obtained, and the water volume deviation of the water source pumping station in the previous ten-day period was calculated based on historical water volume records to formulate the ten-day water volume target.

[0060] Step 4: Establish an economic operation model for water source pumping stations based on time-of-use pricing. See the economic operation model framework for water source pumping stations. Figure 2 As shown, the ten-day water extraction volume allocation layer provides the ten-day water extraction volume target to the start-up combination decision layer based on adjustments to the engineering water dispatch plan and the water extraction volume deviation of the previous ten-day period. The start-up combination decision layer, based on the ten-day water extraction volume target and the time-of-use electricity pricing policy, optimizes the start-up combination scheme for each time period within the ten-day period, aiming to minimize the energy consumption and electricity costs of the pumping station. The components of the optimization problem of the start-up combination decision layer are as follows: (1) Decision variables Based on the division of high and low electricity price periods, the number of pumping stations in operation during each period remains constant. The number of pumping stations in operation X(i) during each period is used as the decision variable, where i is the period number. Each time the model is called, it determines the daily operation combination for the next two ten-day periods. Therefore, the total number of decision variables is 60, i.e., i = 1-60.

[0061] (2) Objective function The objective function is to minimize the energy consumption and electricity cost of pump station operation within the decision domain. (19), In the formula, i is the time period number, 1≤i≤60; X(i) is the number of pumping stations in operation during the i-th time period; P(i) is the single pumping power during the i-th time period, kW; E(i) is the average electricity price during the i-th time period, yuan / kWh; T s (i) represents the length of the i-th time period, h.

[0062] The calculation of the single pump lifting power P(i) needs to consider the influence of the number of pumps in parallel on the pumping flow, efficiency and power of the pumping station, as shown in equations (20)-(22): (20), (twenty one), (twenty two), In the formula, H pumpstation Q is the pumping head of a pumping station with multiple pumps connected in parallel, measured in meters. pumpstation The pumping flow rate of a pumping station after multiple pumps are connected in parallel, in m 3 / s;η pumpstation The pumping station efficiency is calculated by connecting multiple pumps in parallel; ρ is the density of water, taken as 1000 kg / m³. 3 g is the acceleration due to gravity, taken as 9.8 m / s². 2 η0 is the motor efficiency, taken as 0.95.

[0063] (3) Constraints Three types of constraints are considered: ① Number of pumps in operation: to limit the number of pumps in operation and reduce the frequency of pump station start-up and shutdown; ② Engineering safety constraints: to consider the single jump range of the number of pumps in operation and the storage capacity limit of the main water conveyance canal, to ensure the safety of water level during the operation of the main water conveyance canal; ③ Ten-day water delivery volume constraints: to respond to the engineering ten-day water delivery volume scheduling plan and reduce the deviation of ten-day water delivery volume.

[0064] ① Constraint on the number of machines in operation i) The number of pumps operating at any given time period must not exceed the maximum limit for the number of pumps operating: (twenty three), ii) The number of pumping units operating during the high electricity price period at the beginning of the ten-day period should be equal to the number operating during the high electricity price period at the end of the previous ten-day period, thereby reducing the frequency of pumping station unit start-ups and shutdowns: (twenty four), In the formula, X(1) represents the number of generating units started during the period of high electricity prices at the beginning of the ten-day period; X1 represents the number of generating units started during this period. last This refers to the number of pump stations that were in operation during the period of high electricity prices at the end of the previous ten-day period.

[0065] iii) The number of pumping units operating during the high-price period at the end of each day within a ten-day period should be equal to the number of pumping units operating during the high-price period at the beginning of the next day, thereby reducing the frequency of pumping station start-ups and shutdowns: (25), In the formula, n is the number of days in the decision domain, n=1-19.

[0066] ② Engineering safety constraints i) Limit the single jump in the number of pumps started at a water source pumping station: (26) ii) It is necessary to ensure that the channel storage volume fluctuates within the safe range of the storage capacity at all times: (27) In the formula, Storage(i) represents the channel storage capacity at the end of time period i, in ten thousand m³. 3 Storage min To set the lower limit for storage capacity, 3.599 million m³ is used. 3 Storage max To determine the upper limit of the storage capacity, 6.013 million m³ is used. 3 .

[0067] ③ Ten-day water extraction volume constraint Within the decision-making domain, the pumping volume per ten-day period should be within the allowable deviation range of the ten-day target pumping volume: (28) (29) In the formula, Q(i) is the water pumping flow rate of the water source pumping station in the i-th time period, m 3 / s;W target1 The total water extraction target for the first ten-day period within the decision domain, considering the ten-day water allocation plan and the deviation from the previous ten-day water extraction, is given by the ten-day water extraction allocation layer, m. 3 W target1 The total water extraction target for the second ten-day period within the decision domain is set solely based on the ten-day water allocation plan and is provided by the ten-day water extraction configuration layer, m. 3 α represents the allowable deviation of the ten-day water extraction volume, set at 5%.

[0068] (4) Solution algorithm The objective function was solved using the ga function of the genetic algorithm. After debugging, the population size of the genetic algorithm was set to 5000, the maximum number of iterations was set to 200, the number of iterations to stop was set to 30, and other parameters were set to the default values ​​of the algorithm.

[0069] (5) Optimization strategy Each time the model is invoked, it determines the startup combination scheme for the next two ten-day periods, but only the decision scheme for the first ten-day period is output and executed. The above optimization solution process is repeated at the beginning of the next ten-day period.

[0070] Step 5: Based on the model optimization results, guide the operation of the pumping station. At the beginning of each ten-day period, data such as the main water conveyance canal's water storage capacity, the ten-day water allocation plan, the previous ten-day water extraction deviation, and the number of pumping stations in operation at the end of the previous ten-day period are obtained and used as input parameters for the economic operation model of the water source pumping stations. After model optimization and solution, the optimized decision-making results of the daily operation combination scheme for each time period of the ten-day period are output, guiding the start-up and shutdown process of the water source pumping stations within the ten-day period. At the beginning of the next ten-day period, steps three through five are repeated.

[0071] To verify the optimization effect of this embodiment on the economic operation and scheduling of water source pumping stations, the test conditions of the embodiment are designed as follows: (1) The simulation test period is one month. It is assumed that the water allocation plan for the first ten days, middle ten days and last ten days remains unchanged, and the water supply plan for each ten-day period is 67.5m³. 3 / s; (2) The water level in the pump station's intake pool is always at the design water level of 1816.54m; (3) Considering unfavorable conditions, it is assumed that at the beginning of the first ten days of the month, the initial water storage capacity of the main water conveyance canal is the minimum storage volume, i.e., 3.599 million m³. 3 .

[0072] Two conventional operation methods were tested and compared with the economical operation and scheduling method for water source pumping stations proposed in this invention. The two conventional operation methods are described below: Standard Operation Plan A: Without considering time-of-use pricing, prioritizing the engineering safety of the water source pumping stations and the main water conveyance canal, and aiming to fully utilize the storage capacity of the main water conveyance canal. At a fixed time each day, it is determined whether to adjust the number of pumping stations in operation. If maintaining the current number of pumping stations ensures that the main water conveyance canal will not experience a storage overload event within the next day, then the number of pumping stations remains unchanged; otherwise, one pump is added or removed.

[0073] Standard Operation Plan B: Considering time-of-use pricing, prioritizing the engineering safety of the pumping stations and water conveyance system, and aiming to reduce operating costs by utilizing time-of-use pricing policies. The number of pumps in operation will be adjusted no more than twice per day, with one fewer pump operating during peak electricity price periods compared to peak periods.

[0074] The test results of the economical operation and scheduling method for water source pumping stations proposed in this embodiment are shown in the figure. Figures 4-6 The number of pumping stations in operation varies throughout the day depending on electricity prices. During periods of low electricity prices, more pumps are in operation, with a maximum of seven pumps. At this time, the pumping flow rate exceeds the flow rate along the main canal, and the excess water is stored in the main canal. During periods of high electricity prices, fewer pumps are in operation, with a minimum of three pumps. At this time, the pumping flow rate is less than the flow rate along the main canal, and the water stored in the main canal during the low-price period is used to supplement the water supply to users. The maximum fluctuation in the number of pumps in operation between high and low electricity price periods is four pumps. The number of pumps in operation at the beginning of each day during the high-price period is equal to the number of pumps in operation at the end of the previous day during the high-price period, thus meeting the constraint requirements for the number of pumps in operation. Since the initial storage capacity of the main water conveyance canal is the minimum volume value, if the number of pumps is too small, the water pumping flow of the pumping station will be less than the water distribution flow along the main canal, and the canal storage capacity will be lower than the safety limit, violating the engineering safety constraints. Therefore, the number of pumps to be started during the high electricity price period at the beginning of the first day should be at least 5, which is the optimization result of the model considering engineering safety constraints and operating economy.

[0075] The comparison results with the two conventional operation methods are shown in Table 2. The monthly energy consumption and unit water pumping energy consumption of the economic operation and scheduling method of the water source pumping station proposed in this invention are significantly lower than those of the two conventional operation methods, and the utilization rate of the main canal's storage capacity is as high as 98.6%, with a monthly water pumping deviation rate of only 0.72%.

[0076] Table 2 Comparison Results of Multiple Methods Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as object-oriented programming languages ​​like Java, C++, Python, and interpreted scripting languages ​​like JavaScript.

[0077] This application is described with reference to flowchart illustrations and / or block diagrams of methods, electronic devices (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing electronic device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing electronic device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0078] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing electronic device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing electronic device to cause a series of operational steps to be performed on the computer or other programmable electronic device to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable electronic device for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0080] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0081] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for economical operation and scheduling of water source pumping stations based on time-of-use pricing, characterized in that, include: Based on the preliminary design report of the water source pumping station, obtain the design data of the water source pumping station and the safe operation conditions of the main water conveyance canal; Based on the time-of-use electricity pricing policy of the area where the water source pumping station is located, high and low electricity price periods are divided. Based on the past operating data and operation plan of the water source pumping station, obtain the water lifting volume deviation and ten-day water volume scheduling plan of the water source pumping station in the previous ten-day period; An economic operation model for water source pumping stations based on time-of-use pricing is constructed. This model adopts a two-layer architecture, including a water pumping volume allocation layer and a start-up combination decision layer. The water pumping volume allocation layer determines the ten-day water pumping volume target based on the previous ten-day water pumping volume deviation and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the pumping station's energy consumption and electricity costs, using the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target as constraints. Solve the objective function of the economic operation model of the water source pumping station to obtain the start-up combination scheme of the water source pumping station for each time period of each day within a ten-day period; The water source pumping stations are scheduled for economical operation based on the daily operating combination plan for each time period within a ten-day period.

2. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing according to claim 1, characterized in that: The design data of the water source pumping station includes the number of pump units equipped in the pumping station, the prototype energy characteristic curve of the pump, the layout of the pumping station's inlet and outlet water system, and the calculation results of the hydraulic loss of the inlet and outlet water system. Based on the prototype energy characteristic curve of the water pump, the flow-head curve and flow-efficiency curve of a single water pump are obtained by fitting; based on the hydraulic loss calculation results of the inlet and outlet water system, the pipeline characteristic curve of the pump station inlet and outlet water system is obtained by fitting. The safe operation conditions of the main water conveyance canal include the upper and lower limits of the water storage capacity of the main water conveyance canal, and the limit on the single jump amplitude when adjusting the number of pumps started at the water source pumping station. The upper and lower limits of the water storage capacity of the main water conveyance canal are determined based on the preliminary design report of the water source pumping station, and the limit on the single jump amplitude of the number of pumps started is determined based on the safety of the non-steady flow transition process of the main water conveyance canal under the step flow boundary and the operation and management requirements of the pumping station.

3. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing according to claim 2, characterized in that: Based on the prototype energy characteristic curve of the water pump, the performance curve of a single water pump is fitted, namely the flow-head curve shown in equation (1) and the flow-efficiency curve shown in equation (2); based on the hydraulic loss calculation results of the inlet and outlet water system, the pipeline characteristic curve of the pump station inlet and outlet water system is fitted, as shown in equation (3), and the expression is as follows: （1）， （2）， （3）， Where A1, A2, A3 and B1, B2, B3 are fitting coefficients, and Q is the water pump flow rate; For single-pump water lifting head; This refers to the single-pump water lifting efficiency; The water inlet and outlet systems require a head; The difference in water levels between the inlet and outlet pools of the pumping station. , The water level in the inlet pool. This refers to the water level in the outlet pool. The hydraulic losses in the inlet and outlet water system pipelines are expressed as... S is the resistance coefficient of the pipeline system.

4. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing as described in claim 1, characterized in that: The process of constructing the economic operation model of the water source pumping station includes: Based on the division of high and low electricity price periods, the number of pumping stations in operation during each high and low electricity price period remains unchanged. The number of pumping stations in operation during each high and low electricity price period, X(i), is the decision variable, where i is the period number. The economic operation model of the water source pumping station makes a decision on the daily operation combination scheme of the water source pumping station for each of the next two ten-day periods (20 days). Each day is divided into k high and low electricity price periods, and the total number of decision variables is 20k, i.e., i=1-20k. The objective function for minimizing the energy consumption and electricity cost of pump station operation is shown in equation (4): （4）， In the formula, i is the time period number, 1≤i≤20k; X(i) is the number of pumping stations in operation during the i-th time period; P(i) is the single pumping power during the i-th time period; E(i) is the average electricity price during the i-th time period; T s (i) represents the length of the i-th time period; The calculation of the single pump lifting power P(i) needs to consider the impact of the number of pumps in parallel on the pumping flow, efficiency and power of the pumping station. It is obtained by combining the pumping head, pumping flow and operating efficiency of the pumping station after multiple pumps are connected in parallel with the density of water, gravitational acceleration and motor efficiency.

5. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing according to claim 4, characterized in that: The calculation formulas for the single pump water lifting power P(i) are shown in equations (5) to (7): （5）， （6）， （7）， In the formula, H pumpstation The pumping head of a pumping station with multiple pumps connected in parallel; Q pumpstation η is the water flow rate of a pumping station after multiple pumps are connected in parallel. pumpstation ρ is the pumping station efficiency after multiple pumps are connected in parallel; g is the density of water; η0 is the acceleration due to gravity; and η0 is the efficiency of the electric motor.

6. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing according to claim 5, characterized in that: The upper and lower limits on the number of pump units in operation are used to limit the number of units in operation and reduce the frequency of pump station start-up and shutdown. Specifically: The number of pumps operating at any given time period must not exceed the maximum limit. （8）， In the formula, N max This refers to the maximum number of pumps allowed to be operated during normal operation of the water source pumping station. The number of pumping units operating during the high electricity price period at the beginning of the ten-day period should be equal to the number operating during the high electricity price period at the end of the previous ten-day period, thereby reducing the frequency of pumping station unit start-ups and shutdowns. （9）， In the formula, X(1) represents the number of generating units started during the period of high electricity prices at the beginning of the ten-day period; X last This refers to the number of pump stations that were in operation during the period of high electricity prices at the end of the previous ten-day period; The number of pumping units operating during the peak electricity price period at the end of each day within a ten-day period should be equal to the number operating during the peak electricity price period at the beginning of the following day, thereby reducing the frequency of pump station start-ups and shutdowns. （10）， In the formula, n is the number of days in the decision domain, n = 1 - 19; The aforementioned engineering safety constraints are used to consider the single jump amplitude of the number of pump stations in operation and the storage capacity limit of the main water conveyance canal, to ensure the water level safety during the operation of the main water conveyance canal, specifically: Limit the single jump in the number of pumps started at a water source pumping station: （11）， In the formula, Limits the single jump in the number of pump stations in operation; To ensure the safety of the main water conveyance canal's water level, the canal's storage capacity must fluctuate within the allowable storage range at all times. （12）， In the formula, Let be the storage capacity of the main water conveyance canal during the i-th time period; This is the lower limit of the water storage capacity; This is the upper limit of the water storage capacity; Water storage capacity of the main water conveyance canal at different times The calculation method is as follows: （13）， In the formula, This represents the initial storage capacity of the main water conveyance canal at the beginning of the ten-day period; Let the total water distribution flow along the main water conveyance canal during the i-th time period be denoted as . The ten-day water extraction target constraint is used to respond to the engineering ten-day water extraction scheduling plan and reduce the deviation of the ten-day water extraction volume, specifically as follows: The water pumping volume of pumping stations within the decision-making area per ten-day period should be within the allowable deviation range of the ten-day target water pumping volume: （14）， （15）， In the formula, Let be the water pumping flow rate of the water source pumping station in the i-th time period; The water extraction target for the first ten days within the decision domain is given by the water extraction allocation layer; The target water extraction volume for the second ten-day period within the decision domain is set solely based on the ten-day water volume scheduling plan and is provided by the water extraction volume allocation layer; α represents the allowable deviation of the ten-day water extraction volume. The water extraction target for the first ten-day period is the sum of the average water extraction target value for the first ten-day period and the deviation of the water extraction volume from the previous ten-day period. The average water extraction target value for the first ten-day period is the average water extraction value for the ten-day period. The total monthly water pumping target of the water source pumping station is obtained based on the monthly water volume scheduling plan of each month. The total monthly water pumping target is then evenly distributed to each ten-day period to obtain the ten-day average water pumping target.

7. The method for economical operation and scheduling of water source pumping stations based on time-of-use pricing according to claim 1, characterized in that: A genetic algorithm is used to solve the objective function of the economic operation model of the water source pumping station to obtain integer solutions, thereby obtaining the daily operation combination scheme of the water source pumping station for each time period within a ten-day period; In the economic operation scheduling of water source pumping stations, a rolling optimization strategy is adopted. Each time the economic operation model of the water source pumping station is called, the start-up combination scheme for the next two weeks is decided, but only the decision scheme for the first week is output and executed; the above optimization solution process is repeated at the beginning of the next week.

8. A time-of-use pricing-based economic operation scheduling system for water source pumping stations applicable to the method described in any one of claims 1-7, characterized in that: It includes modules for obtaining design data of water source pumping stations and safe operation conditions of main water conveyance canals, modules for dividing high and low electricity price periods, modules for obtaining water pumping volume deviation and ten-day water volume scheduling plans, modules for constructing economic operation models of water source pumping stations, modules for solving economic operation models, and modules for economic operation scheduling. The module for obtaining design data of water source pumping stations and safe operation conditions of main water conveyance canals acquires design data of water source pumping stations and safe operation conditions of main water conveyance canals based on the preliminary design report of the water source pumping station. The high and low electricity price time period division module divides the high and low electricity price time periods according to the time-of-use electricity price policy of the area where the water source pumping station is located; The module for obtaining the water pumping deviation and ten-day water volume scheduling plan obtains the water pumping deviation and ten-day water volume scheduling plan of the water source pumping station in the previous ten-day period based on the past operating data and operating plan of the water source pumping station. The water source pumping station economic operation model construction module constructs an economic operation model for water source pumping stations based on time-of-use electricity pricing. This model adopts a two-layer architecture, including a water pumping volume configuration layer and a start-up combination decision layer. The water pumping volume configuration layer determines the ten-day water pumping volume target based on the previous ten-day water pumping station's pumping volume deviation and the ten-day water scheduling plan, and transmits this target to the start-up combination decision layer. The start-up combination decision layer, based on the water source pumping station's design data and the results of high and low electricity price time periods, establishes an objective function with the goal of minimizing the pumping station's operating energy consumption and electricity costs, using the upper and lower limits of the number of pump units in operation, the safe operation conditions of the main water conveyance canal, and the ten-day water pumping volume target as constraints. The economic operation model solving module solves the objective function of the economic operation model of the water source pumping station to obtain the start-up combination scheme of the water source pumping station for each time period of each day within a ten-day period. The economic operation scheduling module performs economic operation scheduling of water source pumping stations based on the daily operating combination scheme of water source pumping stations within a ten-day period.

9. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to implement the economic operation scheduling method for water source pumping stations based on time-of-use pricing as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the economic operation scheduling method for water source pumping stations based on time-of-use pricing as described in any one of claims 1-7.

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