A multi-time scale hybrid energy storage capacity optimization configuration method for wind-solar-pumped storage system

Abstract

This invention discloses a multi-timescale hybrid energy storage capacity optimization configuration method for wind-solar-cascade hydropower systems. This method constructs models for hydropower unit head loss, ramping constraints, and vibration safety zones; and establishes a two-layer optimization configuration model: an inner layer constructs a day-ahead pumped storage optimization configuration model; and an outer layer constructs an intraday electrochemical energy storage optimization configuration model. The inner layer, through the coordinated scheduling of cascade hydropower and pumped storage, mitigates long-cycle, large-amplitude fluctuations in wind and solar power; the outer layer utilizes the rapid response characteristics of electrochemical energy storage to compensate for short-term, high-frequency, small-amplitude power disturbances. This method fully leverages the regulation capabilities of hydropower and the synergistic advantages of hybrid energy storage, reducing system curtailment rates and improving load matching. Through linearization processing and the Gurobi solver, this method effectively solves the optimization problem of energy storage configuration in wind-solar-cascade hydropower systems, providing reliable technical support for the optimized configuration and efficient utilization of energy storage in clean energy bases.

Description

Technical Field

[0001] This invention belongs to the field of energy storage configuration technology for wind-solar-cascade hydropower systems, and in particular relates to a method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems. Background Technology

[0002] In wind-solar-cascade hydropower complementary systems, the optimized configuration of energy storage is key to improving the renewable energy absorption capacity and system operational stability. Currently, commonly used technologies in the industry mainly focus on the configuration of single energy storage forms and the construction of simplified system models.

[0003] In hybrid energy systems incorporating wind, solar, and cascade hydropower, energy storage configuration research primarily focuses on pumped storage, optimizing its capacity and operational strategies to mitigate renewable energy output fluctuations and assist in grid peak shaving. However, when considering hybrid energy storage configurations, most methods employ a single-timescale optimization framework for competitive allocation, resulting in the configuration of only the most advantageous storage systems. Furthermore, these configuration methods fail to construct a nested decision-making system combining day-ahead planning and intraday rolling adjustments, leading to insufficient matching between the technical characteristics of energy storage and the fluctuation characteristics of renewable energy across different timescales. This makes it difficult to simultaneously and efficiently mitigate both long-term, large-amplitude power deficits and short-term, high-frequency power fluctuations across the entire frequency band. Moreover, existing research often uses simplified linear or aggregate models when dealing with cascade hydropower, failing to accurately characterize the start-up and shutdown characteristics of hydropower units, head effects, flow delays, and reservoir capacity coupling relationships. This limits the potential for exploring the deep synergistic potential between the flexible regulation capabilities of cascade hydropower and hybrid energy storage. In summary, the existing technologies have the following problems: when configuring energy storage in wind-solar-cascade hydropower systems, they are usually limited to a single pumped storage form, failing to fully consider the complementary advantages of new energy storage technologies such as battery energy storage to form a hybrid energy storage system; the configuration optimization of hybrid energy storage is mostly based on a single time scale, lacking an optimization framework that nests multiple time scales from day-ahead to intraday, making it difficult to achieve accurate matching of energy storage resources with the demand for smoothing fluctuations across the entire time spectrum; the cascade hydropower model used in the configuration process is too simplified, failing to accurately represent its complex operational constraints and flexible adjustment capabilities, thus failing to fully explore the deep synergistic potential between hydropower and hybrid energy storage.

[0004] Developing a hybrid energy storage optimization method suitable for wind-solar-cascade hydropower systems requires overcoming challenges such as multi-timescale coupled modeling, synergistic effects of multiple hybrid energy storage technologies, and detailed characterization of complex hydropower systems. Specifically, the difficulties lie in designing an optimization framework that tightly nests day-ahead and intraday timescales, capable of simultaneously handling long-term energy management and short-term power support issues; establishing a mathematical model that accurately reflects the rapid response of battery energy storage, the large-capacity storage of pumped hydro, and the complex hydraulic and electrical coupling relationships of cascade hydropower units; therefore, a multi-timescale hybrid energy storage capacity optimization method for wind-solar-cascade hydropower systems is needed to address these challenges. Summary of the Invention

[0005] The technical problem this invention aims to solve is to provide a method for optimizing the configuration of hybrid energy storage capacity across multiple time scales in wind-solar-cascade hydropower systems. Through the scientific configuration of hybrid energy storage and multi-time-scale coordinated scheduling, it can more economically and efficiently mitigate fluctuations in renewable energy output, thereby improving the system's power supply reliability and operational stability. Simultaneously, it deeply explores the synergistic potential between cascade hydropower and hybrid energy storage, providing reliable technical support for the optimized configuration and efficient utilization of energy storage in clean energy bases.

[0006] To achieve the above-mentioned technical effects, the technical solution adopted by the present invention is as follows: A method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems includes the following steps: S1. Construct a day-ahead hybrid pumped storage optimization configuration model to optimize the pumped storage configuration capacity and system operation plan using a first preset time scale: The constructed day-ahead hybrid pumped storage optimization configuration model includes a day-ahead objective function aimed at maximizing the system's daily net operating revenue, and corresponding day-ahead constraints. The day-ahead objective function is constructed based on the difference between the system's daily operating revenue and its daily operating cost, which includes the operation and maintenance costs of cascade hydropower stations and the configuration and maintenance costs of hybrid pumped storage. The day-ahead constraints include at least cascade hydropower constraints, hybrid pumped storage constraints, and system power balance constraints. S2, Construct an intraday electrochemical energy storage optimization configuration model. Based on the optimization results of the day-ahead hybrid pumped storage optimization configuration model, optimize the configuration power and capacity of electrochemical energy storage using a second preset time scale. The first preset time scale is longer than the second preset time scale to achieve synergy between long-cycle fluctuation smoothing and short-cycle power compensation. The intraday electrochemical energy storage optimization configuration model includes an intraday objective function constructed with the goal of maximizing the intraday system net revenue, and corresponding intraday constraints. The intraday objective function is constructed based on the investment and maintenance costs of electrochemical energy storage, intraday output adjustment costs, and the total intraday operating revenue of the system. The intraday constraints include at least the intraday operating constraints of cascade hydropower and pumped storage, the operating constraints of electrochemical energy storage, and the synergistic operating constraints of pumped storage and electrochemical energy storage. S3 linearizes the nonlinear constraints in the daytime hybrid pumped storage optimization configuration model and the intraday electrochemical energy storage optimization configuration model, transforming them into a mixed integer linear programming model. S4. Based on the linearized mixed integer linear programming model, the Gurobi solver is used to solve the day-ahead hybrid pumped storage optimization configuration model and the intraday electrochemical energy storage optimization configuration model, resulting in a hybrid energy storage optimization configuration scheme that includes pumped storage capacity, electrochemical energy storage power and capacity.

[0007] Preferably, in step S1, the objective function formula is as follows: ; In the formula, The system's daily net operating revenue; For the daily operating revenue of the system; This refers to the daily operating cost of the system. The total system operating cost includes the system operating cost and the configuration cost of the hybrid pumped storage system, as shown in the following expression: ; ; ; ; In the formula, For the first The unit output maintenance cost of a hydroelectric power station; The number of hybrid pumped storage units; Maintenance cost per unit power of pumped storage; This is the upper limit for the power generation capacity of hybrid pumped storage hydroelectric power generation. This is the annualized coefficient for pumped storage; Designed for pumped storage life; The discount rate; The system's operating revenue expression is as follows: ; ; ; ; In the formula, The cost of penalties for power curtailment; These represent the total day-ahead output of wind power and solar power at sections 1 and 2, respectively. These are the hybrid pumped storage power generation capacity and pumping power, respectively. This represents the current generating capacity of the hydroelectric generator units. This refers to the amount of abandoned electricity.

[0008] Preferably, in step S1, the cascade hydropower constraints are used to characterize the complex operating characteristics of cascade hydropower stations, specifically including one or more of the following constraints: water quantity constraint, outflow constraint, reservoir capacity constraint, hydropower unit output characteristic constraint considering head and flow, water level constraint, unit start-up and shutdown constraint, nonlinear relationship constraint between lower reservoir water level and outflow, nonlinear relationship constraint between upper reservoir water level and reservoir capacity, and hydropower unit vibration zone output constraint. Hybrid pumped storage constraints are used to characterize the operating characteristics of pumped storage units, specifically including pumping power constraints, power generation constraints, and reservoir capacity constraints shared with cascade hydropower projects.

[0009] Preferably, in step S2, the intraday objective function includes: Intraday system net revenue includes electrochemical investment and maintenance costs, intraday deviation adjustment costs, and total intraday system operating revenue, as shown in the following formula: ; ; ; ; ; ; ; In the formula, Investment cost for electrochemical energy storage capacity; For operation and maintenance costs; To expand the daytime schedule to 96 time slots; Adjust costs to make efforts within the day; Cost per unit capacity; This is the rated capacity of the electrochemical energy storage. Design life; This is the rated power for electrochemical energy storage; The daily operating revenue of the system needs to be supplemented by the daily operating revenue of electrochemical energy storage, based on the daily operating revenue of the previous day. The specific mathematical expression is as follows: ; ; In the formula, It consists of 96 time periods, with a time scale of 15 minutes; For the daily operating revenue of electrochemical energy storage.

[0010] Preferably, in step S2, the electrochemical energy storage operation constraints include charge / discharge power constraints and energy storage state of charge constraints; Charge and discharge power constraints are used to limit the charge and discharge power of electrochemical energy storage to not exceed its rated power. Energy storage state of charge constraints are used to describe the dynamic changes in the amount of electricity stored in electrochemical energy and to ensure that the amount of electricity stored is within a safe operating range. The synergistic operation constraint of pumped hydro storage and electrochemical energy storage is used to ensure that the two do not operate in a state of simultaneous charging or discharging during the day.

[0011] Preferably, in step S3, the linearization process includes one or more of the following methods: A piecewise linearization method is used to handle the nonlinear relationship between reservoir capacity and water level; A piecewise linearization method is used to process the squared head loss term of the hydropower unit. The nonlinear term of the product of flow rate and head in the power output characteristics of hydropower units is handled by introducing a weight matrix. The Big M method is used to handle the multiplication terms of logical variables and continuous variables in energy storage power constraints.

[0012] Preferably, the piecewise linearization method for handling the nonlinear relationship between reservoir capacity and water level specifically includes: Relationship between water level and flow rate in cascade hydropower projects Piecewise linear processing is used, and the specific expression is as follows: ; ; ; In the formula, This is a nonlinear function relating the water level and capacity of the upper reservoir.

[0013] Preferably, the piecewise linearization method for processing the squared head loss term of the hydropower unit specifically includes: For water level constraints The linearization of the squared head loss term is as follows: ; ; ; In the formula, The power generation flow segmentation matrix; The square matrix represents the power generation flow rate. Weight matrix; The water level of the upper reservoir of the cascade hydropower project; The water level of the reservoirs in the cascade hydropower project; This is due to the loss of water head.

[0014] Preferably, the method of introducing a weight matrix to handle the nonlinear term of the product of flow rate and head in the power output characteristics of a hydropower unit specifically includes: For output constraints The product of flow rate and head is used to linearize the above nonlinear constraints, defining the flow rate matrix. Water head matrix The linearization process is as follows: ; ; In the formula, This is the hydropower generation coefficient; This is the weight matrix; No. Taiwan hydroelectric power unit in the Power generation output during a given period; For power generation head; For hydroelectric conversion efficiency; This is the acceleration due to gravity.

[0015] Preferably, the method of using the Big M method to handle the multiplication terms of logical variables and continuous variables in energy storage power constraints specifically includes: Constraints on pumping and power generation and and charging / discharging power constraints and The Big M method is used for linearization, and the specific formula is as follows: ; In the formula, For pumped storage power stations in the first Pumping power during a given time period; For pumped storage power stations in the first Power generation during a given time period; This is the maximum generating capacity of the pumped storage power station; This is the maximum pumping power of the pumped storage power station; The charging and discharging power for electrochemical energy storage; Rated power for electrochemical energy storage; The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a charging state. The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a discharge state. A value of 1 indicates that the pumped storage power station is in power generation mode. A value of 1 indicates that the pumped storage power station is in the pumping state.

[0016] The beneficial effects of this invention are as follows: 1. This invention effectively solves the problems of single configuration mode, fragmented time scale, and oversimplification in existing technologies by constructing a hybrid energy storage capacity optimization configuration method based on wind-solar-cascade hydropower systems. Its core lies in proposing a multi-time-scale nested optimization framework from day-ahead to intraday, and achieving precise synergy between refined modeling of cascade hydropower and the characteristics of hybrid energy storage technology.

[0017] 2. This invention achieves the organic unity of long-term energy dispatch and short-term power regulation by establishing a nested decision-making mechanism of day-ahead planning and intraday rolling correction. This framework can allocate long-term, large-scale power deficits to large-capacity energy storage such as pumped storage, while entrusting short-term, high-frequency power fluctuations to rapidly responding electrochemical energy storage, thereby achieving full-frequency, high-efficiency smoothing of renewable energy output and significantly improving the system's power balance capability and operational stability.

[0018] 3. This invention overcomes the limitations of single energy storage methods, fully leveraging the complementary advantages of pumped storage (large-scale, long-cycle storage) and battery storage (rapid response, precise regulation). It employs a refined cascade hydropower model, accurately accounting for complex constraints such as unit characteristics, head effect, flow delay, and reservoir capacity coupling. This allows the optimization model to fully exploit and utilize the inherent flexible regulation capabilities of cascade hydropower, enabling deep synergy with hybrid energy storage to jointly address renewable energy fluctuations, enhancing the flexibility and reliability of the entire complementary system, and improving the comprehensive utilization efficiency of hydropower resources.

[0019] 4. Through the aforementioned multi-resource, multi-timescale collaborative optimization, this invention effectively reduces the overall system operating cost and decreases wind and solar power curtailment. Simultaneously, the optimized energy storage configuration and operation strategy provides the power grid with additional regulation capacity and ancillary services, enhancing the system's ability to accommodate a high proportion of renewable energy and strongly supporting the construction of a new power system.

[0020] 5. This invention demonstrates outstanding practical value in improving the economic efficiency, safety, and green and low-carbon level of system operation. Its methodological framework has strong versatility and scalability, providing important theoretical basis and decision support for the planning and operation of power systems with a high proportion of renewable energy. Attached Figure Description

[0021] Figure 1 This is a framework diagram of the wind-solar-cascade water system of this invention patent; Figure 2 This is a flowchart of the solution process for this invention patent; Figure 3 This is a load power curve provided in an embodiment of the present invention; Figure 4 This is a predicted power output map of wind power and photovoltaic clusters provided in an embodiment of the present invention; Figure 5 This is a daytime running diagram of section 1 under mode 1 provided in the embodiment of the present invention; Figure 6 This is a daytime running diagram of section 2 under mode 1 provided in this embodiment of the invention; Figure 7 This is a daytime running diagram of section 3 under mode 1 provided in this embodiment of the invention; Figure 8 This is the daytime running diagram of section 4 under mode 1 provided in this embodiment of the invention; Figure 9 This is the intraday operation diagram of section 1 under mode 3 provided in the embodiment of the present invention; Figure 10 This is the intraday operation diagram of section 2 under mode 3 provided in the embodiment of the present invention; Figure 11 This is the intraday operation diagram of section 3 under mode 3 provided in the embodiment of the present invention; Figure 12 This is the intraday operation diagram of section 4 under mode 3 provided in the embodiment of the present invention. Detailed Implementation

[0022] Example 1: like Figure 2 As shown, a multi-timescale hybrid energy storage optimization configuration method for wind-solar-cascade hydropower systems is proposed. This method optimizes the hybrid energy storage capacity configuration for wind-solar-cascade hydropower bases, fully considering the complementary advantages of hybrid energy storage across multiple timescales. A multi-timescale operation strategy for pumped storage and electrochemical energy storage is proposed, and a day-ahead and intraday hybrid energy storage capacity optimization configuration model is established. In the day-ahead phase, the model uses a 1-hour timescale to generate the day-ahead power output plan and pumped storage capacity configuration scheme. In the intraday phase, based on the day-ahead phase, it uses a 15-minute timescale to generate the electrochemical energy storage capacity configuration scheme and the charging and discharging power during operation. The Gurobi solver is used for solving the problem, and simulation calculations are performed under different scenarios. The calculation results demonstrate the advantages of this method, including the following steps: Step 1: Construct a day-ahead hybrid pumped storage optimization configuration model.

[0023] (1) The objective function for the day before: (1) In the formula, The system's daily net operating revenue; For the daily operating revenue of the system; This represents the daily operating cost of the system.

[0024] (a) The total system operating cost includes the system operating cost and the configuration cost of the hybrid pumped storage system, as shown in the following expression: (2) (3) (4) (5) In the formula, For the first The unit output maintenance cost of a hydroelectric power station; The number of hybrid pumped storage units; Maintenance cost per unit power of pumped storage; This is the upper limit for the power generation capacity of hybrid pumped storage hydroelectric power generation. This is the annualized coefficient for pumped storage; Designed for pumped storage life; is the discount rate.

[0025] (b) The system's operating revenue expression is as follows: (6) (7) (8) (9) In the formula, The cost of penalties for power curtailment; These represent the total day-ahead output of wind power and solar power at sections 1 and 2, respectively. These are the hybrid pumped storage power generation capacity and pumping power, respectively. This represents the current generating capacity of the hydroelectric generator units. This refers to the amount of abandoned electricity.

[0026] (2) Day-ahead constraints: 1) Cascade hydropower constraints: (a) Water quantity constraint: Due to watershed flow, the inflow to the downstream hydropower stations in a cascade hydropower system is related to the outflow to the upstream hydropower stations. Let the first... The first hydropower station in Inbound flow during the period is The outflow from the upstream hydropower station is The water quantity constraint can be expressed as: (10) In the formula, The flow propagation coefficient reflects the degree of influence of upstream outflow on downstream inflow. For the water flow from the upstream hydropower station to the first The propagation time of each hydropower station.

[0027] (b) Flow constraints: (11) In the formula, For the first The first hydropower station in Outbound flow during a specific time period; These represent the minimum and maximum outbound flow rates.

[0028] (c) Storage capacity constraints: (12) (13) In the formula, For the first The reservoir in the first Storage capacity for a given period of time; For the first The reservoir in the first Minimum and maximum storage capacity for a given time period.

[0029] (d) Output constraints: (14) (15) In the formula, No. Taiwan hydroelectric power unit in the Power generation output during a given period; For power generation head; For hydroelectric conversion efficiency; It is the acceleration due to gravity; For the first Taiwan hydroelectric power unit in the Minimum and maximum power generation output during a given time period.

[0030] (e) Water level constraints: (16) (17) In the formula, The water level of the upper reservoir of the cascade hydropower project; The water level of the reservoirs in the cascade hydropower project; To lose water head (f) Start-stop constraints: (18) In the formula, For the first Taiwan hydroelectric power unit in the The start-up and shutdown status of the generating units during a given time period; These are the minimum start-up time and minimum downtime of the unit.

[0031] (g) Relationship between reservoir water level and flow rate in cascade hydropower projects: (19) In the formula, This represents the nonlinear relationship between the reservoir water level and the outflow.

[0032] (h) Relationship between water level and flow rate in cascade hydropower projects: (20) In the formula, This is a nonlinear function relating the water level and capacity of the upper reservoir.

[0033] (i) Output constraints in the vibration zone of hydropower units: ;(twenty one) 2) Hybrid pumped storage constraints: (a) Pumping and power generation constraints: ;(twenty two) ;(twenty three) ;(twenty four) (25) In the formula, For pumped storage power stations in the first Pumping power during a given time period; For pumping efficiency; The average head of the pumped storage; For pumped storage power stations in the first Power generation during a given time period; For power generation efficiency; These are the minimum and maximum generating capacities of the pumped storage power station, respectively. These are the minimum and maximum pumping capacities of the pumped storage power station, respectively. This refers to the amount of water flowing into the upper reservoir during pumping. This represents the amount of water flowing out of the upper reservoir during power generation. This paper adopts a hybrid pumped storage system that shares the upper and lower reservoirs of a cascade hydropower project, therefore the same reservoir capacity constraints as those used for cascade hydropower projects are applied.

[0034] (b) Pumped storage state constraints: (26) In the formula, A value of 1 indicates that the pumped storage power station is in power generation mode; A value of 1 indicates that the pumped storage power station is in the pumping state.

[0035] 3) Power balance constraints: (27) In the formula, For the receiving end of the power grid load; This refers to the amount of electricity wasted.

[0036] Step 2: Construct an intraday electrochemical energy storage optimization configuration model.

[0037] (1) Intraday objective function: Intraday system net revenue includes electrochemical investment and maintenance costs, intraday deviation adjustment costs, and total intraday system operating revenue. (28) (29) (30) (31) (32) (33) (34) In the formula, Investment cost for electrochemical energy storage capacity; For operation and maintenance costs; To expand the daytime schedule to 96 time slots; Adjust costs to make efforts within the day; Cost per unit capacity; This is the rated capacity of the electrochemical energy storage. Design life; This is the rated power for electrochemical energy storage.

[0038] The daily operating revenue of the system needs to be supplemented by the daily operating revenue of electrochemical energy storage, based on the daily operating revenue of the previous day. The specific mathematical expression is as follows: (35) (36) In the formula, It consists of 96 time periods, with a time scale of 15 minutes; For the daily operating revenue of electrochemical energy storage.

[0039] (2) Construction of intraday constraints: 1) Constraints of cascade hydropower and pumped storage: The constraints are basically the same as those in the current model, only the time scale needs to be changed to 15 minutes.

[0040] 2) Electrochemical energy storage constraints: (a) Charge and discharge power constraints: (37) (38) (39) (40) In the formula, The charging and discharging power for electrochemical energy storage; Rated power for electrochemical energy storage; The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a charging state. The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a discharge state. This refers to the rated charge / discharge duration.

[0041] (b) Energy storage SOC constraints: (41) (42) (43) (44) In the formula, for The amount of electricity stored in electrochemical energy storage at any given time; The charging efficiency of electrochemical energy storage; Discharge efficiency of electrochemical energy storage; for The charging and discharging power of time-lapse electrochemical energy storage; This refers to the rated capacity of electrochemical energy storage.

[0042] 3) Constraints on the coordinated operation of pumped hydro storage and electrochemical energy storage: (45) In the formula, These represent the pumping and power generation states of the pumped storage hydroelectric power plant during the day.

[0043] Step 3: Model linearization: (1) Linearization of the relationship between reservoir capacity and water level: For equation (20), piecewise linear processing is adopted, and the specific expression is as follows: (46) (47) (48) (2) Linearization of head loss: For equation (17), the linearization of the squared head loss term is as follows: (49) (50) (51) In the formula, The power generation flow segmentation matrix; The square matrix represents the power generation flow rate. Weight matrix.

[0044] (3) Linearization of hydropower generation characteristics: For equation (14) which contains the product of two variables, flow rate and head, the above nonlinear constraints need to be linearized, and the flow rate matrix needs to be defined. Water head matrix The linearization process is as follows: (52) (53) In the formula, This is the hydropower generation coefficient; This is the weight matrix.

[0045] (4) Linearization of energy storage power constraints: For equations (24), (25), (37), and (38), the Big M method is used for linearization, and the specific formulas are as follows: (54) In the formula, It is a constant and satisfies Equations (25), (37), and (38) are also processed in a similar way.

[0046] Step 4: Use the Gurobi solver to perform simulation calculations under different scenarios: The solution process includes: S401, input day-ahead forecast data for wind and solar power loads; S402, linearize the day-ahead model according to equations (46)-(54); S403, according to equations (1)-(27) and (46)-(54), the planned output of the cascade hydropower units and the pumped storage configuration capacity are solved using the Gurobi solver; S404, input intraday forecast data for wind and solar loads; S405, linearize the intraday model according to equations (46)-(54); S406, input the planned output of the cascade hydropower units and the pumped storage configuration capacity calculated in S4.3, and use the Gurobi solver to solve for the power and capacity of the electrochemical energy storage configuration according to equations (28)-(45).

[0047] Example 2: This embodiment is based on a complementary system constructed from cascaded hydropower, two wind power clusters, and two photovoltaic clusters. The system's power output is divided into four sections, where each section represents a transmission constraint boundary defined by the power system's grid topology, voltage level, and power supply area. Sections 1 and 2 are powered by cascaded hydropower units, one wind power cluster, and one photovoltaic cluster, while sections 3 and 4 are powered by cascaded hydropower. The specific relationships are as follows: Figure 1 As shown.

[0048] Based on the above system, the pumped storage and electrochemical energy storage capacities are optimized and configured, with the load power as follows: Figure 3 As shown, the power output of wind and solar new energy sources is as follows: Figure 4 As shown.

[0049] Scene description: 1) Method 1: Configure pumped storage in the day-ahead phase.

[0050] 2) Method 2: Configure electrochemical energy storage in the day-ahead phase.

[0051] 3) Method 3: Based on the pumped storage configured in the day-ahead phase, electrochemical energy storage is configured with a time scale of 15 minutes.

[0052] Scene calculation: This example uses the Gurobi solver for calculation. The specific steps are as follows: S401, input day-ahead forecast data for wind and solar power loads; S402, linearize the day-ahead model according to equations (46)-(54); S403, according to equations (1)-(27) and (46)-(54), the planned output of the cascade hydropower units and the pumped storage configuration capacity are solved using the Gurobi solver; S404, input intraday forecast data for wind and solar loads; S405, linearize the intraday model according to equations (46)-(54); S406, input the planned output of the cascade hydropower units and the pumped storage configuration capacity calculated in S4.3, and use the Gurobi solver to solve for the power and capacity of the electrochemical energy storage configuration according to equations (28)-(45).

[0053] Results analysis: Scenario III is the application of the method of the present invention in the embodiment. The energy storage configuration results of the three scenarios are calculated by the algorithm and are shown in Table 1.

[0054] Table 1: Energy storage configuration results for methods 1-3;

[0055] Option 1 configures pumped-storage units with capacities of 90 MW, 134 MW, 20 MW, and 19 MW at each cross-section. This option has the lowest investment cost and the highest system operating benefit, but also the highest curtailment rate, indicating that while pumped storage alone has good economics, its short-term regulation capability for highly volatile renewable energy is limited. Option 2 adopts a fully electrochemical energy storage configuration, with energy storage capacities of 172MW, 161MW, 53MW, and 37MW at each cross-section. This option significantly increases investment costs, reduces operating benefits to 12.88 million yuan / day, and substantially lowers the curtailment rate. This demonstrates that electrochemical energy storage is highly effective in improving the system's renewable energy absorption capacity, but its economics are significantly affected by energy storage costs. Option 3 uses a hybrid configuration of pumped storage and electrochemical energy storage, adding small-scale, short-term electrochemical energy storage while maintaining the pumped storage capacity. The investment cost of this scheme is 324,700 yuan / day, which is higher than that of the single pumped storage scheme, but significantly lower than that of the all-electrochemical energy storage scheme; the operating revenue reaches 13,445,100 yuan / day, close to that of scheme 1; at the same time, the curtailment rate is further reduced compared to scheme 1, and is the lowest among the three schemes. The results show that hybrid energy storage achieves a good balance between economy and operational flexibility.

[0056] Figure 5-8The figure shows the day-ahead operation results for each section when only pumped storage is configured. As can be seen from the figure, the output changes at each section mainly exhibit typical hourly step-like adjustment characteristics, with relatively gentle power changes between adjacent time periods, indicating a relatively stable overall system operation. During periods when wind and solar output gradually increases, the cascade hydropower reduces generation, and the pumped storage works in concert to absorb excess wind and solar output, without significant power curtailment. Looking at the section operation, in sections 1 and 2, pumped storage and hydropower participate in regulation in tandem, and their output change trends are consistent with those of new energy output, demonstrating that pumped storage plays a role in energy balance and new energy absorption at the day-ahead dispatch level. In sections 3 and 4, the overall system output matches the load change trend of the receiving-end grid, indicating that pumped storage can effectively support the demand of the receiving-end grid at the day-ahead dispatch scale. However, since this scheme only uses day-ahead dispatch with a 1-hour resolution, the power curves of each section in the figure do not reflect the response capability to short-term fluctuations in new energy and load within the hour; their regulation behavior is mainly concentrated at the hourly time scale. Only by configuring pumped storage and adopting day-ahead dispatch, the system's energy balance and overall absorption of new energy sources can be achieved. However, its regulation capability is mainly reflected in a longer time scale, and its ability to characterize and respond to power fluctuations in a short time scale is limited.

[0057] Figure 9-12 The figures show the operational results of the hybrid energy storage system participating in multi-timescale coordinated scheduling. During periods of high renewable energy output, in section 1, electrochemical energy storage frequently participates in power regulation, handling the power fluctuations generated by renewable energy in short timescales, while pumped hydro storage experiences relatively gentle power changes, primarily maintaining a stable operating state. In sections 3 and 4, the total system output curve is highly consistent with the trend of load changes at the receiving end, and the power fluctuation amplitude converges significantly. During periods of relatively gentle load changes, the joint regulation by hybrid energy storage makes the system operation more stable, and no significant power curtailment is observed in the figures. By rationally allocating regulation tasks at different timescales, the hybrid energy storage system can have electrochemical energy storage handle high-frequency, small-amplitude power regulation, while pumped hydro storage is responsible for medium- and long-term energy balance, thereby achieving a simultaneous improvement in system operational stability and renewable energy absorption capacity.

Claims

1. A method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems, characterized in that, Includes the following steps: S1. Construct a day-ahead hybrid pumped storage optimization configuration model to optimize the pumped storage configuration capacity and system operation plan using a first preset time scale: The constructed day-ahead hybrid pumped storage optimization configuration model includes a day-ahead objective function aimed at maximizing the system's daily net operating revenue, and corresponding day-ahead constraints. The day-ahead objective function is constructed based on the difference between the system's daily operating revenue and its daily operating cost, which includes the operation and maintenance costs of cascade hydropower stations and the configuration and maintenance costs of hybrid pumped storage. The day-ahead constraints include at least cascade hydropower constraints, hybrid pumped storage constraints, and system power balance constraints. S2, Construct an intraday electrochemical energy storage optimization configuration model. Based on the optimization results of the day-ahead hybrid pumped storage optimization configuration model, optimize the configuration power and capacity of electrochemical energy storage using a second preset time scale. The first preset time scale is longer than the second preset time scale to achieve synergy between long-cycle fluctuation smoothing and short-cycle power compensation. The intraday electrochemical energy storage optimization configuration model includes an intraday objective function constructed with the goal of maximizing the intraday system net revenue, and corresponding intraday constraints. The intraday objective function is constructed based on the investment and maintenance costs of electrochemical energy storage, intraday output adjustment costs, and the total intraday operating revenue of the system. The intraday constraints include at least the intraday operating constraints of cascade hydropower and pumped storage, the operating constraints of electrochemical energy storage, and the synergistic operating constraints of pumped storage and electrochemical energy storage. S3 linearizes the nonlinear constraints in the daytime hybrid pumped storage optimization configuration model and the intraday electrochemical energy storage optimization configuration model, transforming them into a mixed integer linear programming model. S4. Based on the linearized mixed integer linear programming model, the Gurobi solver is used to solve the day-ahead hybrid pumped storage optimization configuration model and the intraday electrochemical energy storage optimization configuration model, resulting in a hybrid energy storage optimization configuration scheme that includes pumped storage capacity, electrochemical energy storage power and capacity.

2. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 1, characterized in that, In step S1, the objective function formula for the day-ahead period is as follows: ； In the formula, The system's daily net operating revenue; For the daily operating revenue of the system; This refers to the daily operating cost of the system. The total system operating cost includes the system operating cost and the configuration cost of the hybrid pumped storage system, as shown in the following expression: ； ； ； ； In the formula, For the first The unit output maintenance cost of a hydroelectric power station; The number of hybrid pumped storage units; Maintenance cost per unit power of pumped storage; This is the upper limit for the power generation capacity of hybrid pumped storage hydroelectric power generation. This is the annualized coefficient for pumped storage; Designed for pumped storage life; The discount rate; The system's operating revenue expression is as follows: ； ； ； ； In the formula, The cost of penalties for power curtailment; These represent the total day-ahead output of wind power and solar power at sections 1 and 2, respectively. These are the hybrid pumped storage power generation capacity and pumping power, respectively. This represents the current generating capacity of the hydroelectric generator units. This refers to the amount of abandoned electricity.

3. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 2, characterized in that, In step S1, the cascade hydropower constraints are used to characterize the complex operating characteristics of cascade hydropower stations, specifically including one or more of the following constraints: water quantity relationship constraints, outflow constraints, reservoir capacity constraints, hydropower unit output characteristic constraints considering head and flow, water level constraints, unit start-up and shutdown constraints, nonlinear relationship constraints between lower reservoir water level and outflow, nonlinear relationship constraints between upper reservoir water level and reservoir capacity, and hydropower unit vibration zone output constraints. Hybrid pumped storage constraints are used to characterize the operating characteristics of pumped storage units, specifically including pumping power constraints, power generation constraints, and reservoir capacity constraints shared with cascade hydropower projects.

4. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 1, characterized in that, In step S2, the intraday objective function includes: Intraday system net revenue includes electrochemical investment and maintenance costs, intraday deviation adjustment costs, and total intraday system operating revenue, as shown in the following formula: ； ； ； ； ； ； ； In the formula, Investment cost for electrochemical energy storage capacity; For operation and maintenance costs; To expand the daytime schedule to 96 time slots; Adjust costs to make efforts within the day; Cost per unit capacity; This is the rated capacity of the electrochemical energy storage. Design life; This is the rated power for electrochemical energy storage; The daily operating revenue of the system needs to be supplemented by the daily operating revenue of electrochemical energy storage, based on the daily operating revenue of the previous day. The specific mathematical expression is as follows: ； ； In the formula, It consists of 96 time periods, with a time scale of 15 minutes; For the daily operating revenue of electrochemical energy storage.

5. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 4, characterized in that, In step S2, the electrochemical energy storage operation constraints include charge and discharge power constraints and energy storage state of charge constraints; Charge and discharge power constraints are used to limit the charge and discharge power of electrochemical energy storage to not exceed its rated power. Energy storage state of charge constraints are used to describe the dynamic changes in the amount of electricity stored in electrochemical energy and to ensure that the amount of electricity stored is within a safe operating range. The synergistic operation constraint of pumped hydro storage and electrochemical energy storage is used to ensure that the two do not operate in a state of simultaneous charging or discharging during the day.

6. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 1, characterized in that, In step S3, the linearization process includes one or more of the following methods: A piecewise linearization method is used to handle the nonlinear relationship between reservoir capacity and water level; A piecewise linearization method is used to process the squared head loss term of the hydropower unit. The nonlinear term of the product of flow rate and head in the power output characteristics of hydropower units is handled by introducing a weight matrix. The Big M method is used to handle the multiplication terms of logical variables and continuous variables in energy storage power constraints.

7. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 6, characterized in that, The piecewise linearization method for handling the nonlinear relationship between reservoir capacity and water level specifically includes: Relationship between water level and flow rate in cascade hydropower projects Piecewise linear processing is used, and the specific expression is as follows: ； ； ； In the formula, This is a nonlinear function relating the water level and capacity of the upper reservoir.

8. The method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 7, characterized in that, The piecewise linearization method for processing the squared head loss term of hydropower units specifically includes: For water level constraints The linearization of the squared head loss term is as follows: ； ； ； In the formula, The power generation flow segmentation matrix; The square matrix represents the power generation flow rate. Weight matrix; The water level of the upper reservoir of the cascade hydropower project; The water level of the reservoirs in the cascade hydropower project; This is due to the loss of water head.

9. A method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 8, characterized in that, The method of introducing a weight matrix to handle the nonlinear term of the product of flow rate and head in the power output characteristics of hydropower units specifically includes: For output constraints The product of flow rate and head is used to linearize the above nonlinear constraints, defining the flow rate matrix. Water head matrix The linearization process is as follows: ； ； In the formula, This is the hydropower generation coefficient; This is the weight matrix; No. Taiwan hydroelectric power unit in the Power generation output during a given period; For power generation head; For hydroelectric conversion efficiency; This is the acceleration due to gravity.

10. A method for optimizing the configuration of multi-timescale hybrid energy storage capacity for wind-solar-cascade hydropower systems according to claim 9, characterized in that, The Big M method is used to handle the multiplication of logical and continuous variables in energy storage power constraints, specifically including: Constraints on pumping and power generation and and charging / discharging power constraints and The Big M method is used for linearization, as follows: ； In the formula, For pumped storage power stations in the first Pumping power during a given time period; For pumped storage power stations in the first Power generation during a given time period; This is the maximum generating capacity of the pumped storage power station; This is the maximum pumping power of the pumped storage power station; The charging and discharging power for electrochemical energy storage; Rated power for electrochemical energy storage; The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a charging state. The variable is either 0 or 1; a value of 1 indicates that the electrochemical energy storage is in a discharge state. A value of 1 indicates that the pumped storage power station is in power generation mode. A value of 1 indicates that the pumped storage power station is in the pumping state.

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