Scheduling optimization method for long-term and short-term coordination of water, light and storage

Abstract

The invention discloses a water-light-storage long-term and short-term collaborative scheduling optimization method, which belongs to the technical field of hydropower and photovoltaic complementary operation, and comprises the following steps: simulating a short-term typical annual runoff process and a photovoltaic process based on multiple scenes; in real-time economic operation, according to a water-light complementation relation, a priority internet access sequence is made, and a water-light-storage complementation strategy is determined; on the basis of the above steps, a target function with the maximum generating capacity as a target is constructed based on the obtained long-term photovoltaic power abandoning curve and the obtained long-term pumping storage utilization photovoltaic curve, then a water-light-storage complementary system model is constructed by combining constraint conditions, the water-light-storage complementary system model is solved by adopting a discrete differential dynamic programming algorithm, and a medium-and-long-term optimal scheduling sample is obtained; the available energy is adopted as an input variable, so that a complementary scheduling function is fitted; and water resources can be more effectively utilized through the complementary scheduling function, so that the hydroelectric generating capacity is improved. And meanwhile, the scheduling flexibility of the hydropower station can be better matched with the instability of photovoltaic power generation, so that the utilization rate of photovoltaic power generation is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of hydropower and photovoltaic complementary operation, and specifically relates to a scheduling optimization method for long-term and short-term coordinated hydropower and photovoltaic storage. Background Art

[0002] In the context of rapid social and economic development today, global energy demand continues to grow. At the same time, energy crisis and ecological protection pressure have become obstacles to the use of fossil energy. Countries are paying increasing attention to energy security, ecological environment and climate change issues, and green and low-carbon energy has become a global consensus and action goal. The development of renewable energy has been seen as an effective means to meet the growing energy demand and address the challenges of climate change. As clean renewable energy to cope with the volatility and intermittent characteristics of photovoltaics, hydropower, pumped storage and photovoltaic complementary operation can solve the problem of photovoltaic absorption. However, in the long-term scheduling of hydro-photovoltaic storage complementary, quantifying the long-term photovoltaic absorption is the key to accurately calculate the long-term scheduling target of the hydro-photovoltaic storage complementary system. Due to the difficulty in accurately estimating the long-term photovoltaic power abandonment and pumped storage power generation, it is challenging to deduce the long-term scheduling rules of the hydro-photovoltaic storage complementary system.

[0003] The complementarity of photovoltaics, hydropower, and pumped storage is particularly evident in the short term. Research on the joint dispatching model and real-time coordinated control strategy of large-scale photovoltaics, adjustable hydropower stations, and pumped storage stations can effectively meet the target requirements of system flexibility, new energy consumption, and other aspects.

[0004] Based on the literature survey, domestic and foreign scholars have conducted a large number of related studies on the scheduling of multi-energy complementary systems and have achieved rich research results. Existing research mainly focuses on multi-scale optimization scheduling of hydro-photovoltaic complementarity, while research on photovoltaic consumption and electricity prices focuses on the short term. There is a lack of systematic theory and methods for quantifying long-term photovoltaic consumption and accurately estimating long-term power generation after adding pumped storage. Therefore, it is impossible to accurately estimate the long-term photovoltaic and pumped storage grid-connected power generation, which affects the operation and optimization of the long-term complementary system. Summary of the invention

[0005] The purpose of the present invention is to address the problem that the existing technology lacks a system that can quantify long-term photovoltaic consumption and accurately estimate long-term power generation after adding pumped storage, which leads to the inability to accurately estimate the long-term photovoltaic and pumped storage grid-connected power generation. A scheduling optimization method for the long-term and short-term coordination of water, photovoltaic and storage is proposed. By focusing on the core issue of formulating a long-term scheduling strategy for the water, photovoltaic and storage complementary system, the short-term model is scaled up to simulate the long-term photovoltaic power abandonment function and long-term electricity price, and a long-term scheduling model for the water, photovoltaic and storage complementary system is constructed, and the complementary scheduling function is derived with power generation efficiency as the goal. It aims to further improve the scheduling model of the water, photovoltaic and storage complementary system, maximize the benefits of renewable resource utilization, provide a scheduling optimization method for the long-term and short-term coordination of water, photovoltaic and storage, and guide the operation of the water, photovoltaic and storage complementary system.

[0006] In order to solve the above technical problems, the present invention provides a scheduling optimization method for long-term and short-term coordination of hydro-solar-energy storage, including:

[0007] S1. Simulate short-term typical annual runoff process and photovoltaic process based on multiple scenarios;

[0008] S2. In real-time economic operation, the priority order of access to the grid is formulated according to the complementary relationship between water and light, and the complementary strategy between water, light and energy storage is determined;

[0009] S3. Consider multiple scenarios to simulate the short-term typical annual runoff process, photovoltaic process and hydro-PV-storage complementary strategy, and obtain the long-term photovoltaic power abandonment curve and the long-term pumped storage photovoltaic curve;

[0010] S4. Based on the long-term photovoltaic power abandonment curve and the long-term pumped storage photovoltaic curve, an objective function with the maximum power generation as the goal is constructed, and then combined with the constraint conditions to construct a water-solar-storage complementary system model;

[0011] S5. Based on the hydro-solar-storage complementary system model, the discrete differential dynamic programming algorithm is used to solve the hydro-solar-storage complementary system model to obtain the medium- and long-term optimal scheduling samples. The available energy in the medium- and long-term optimal samples is used as the input variable, and the reservoir output is selected as the decision variable to fit the complementary scheduling function.

[0012] Preferably, the photovoltaic process is represented by photovoltaic output, wherein the photovoltaic output calculation formula includes:

[0013]

[0014] Where Ppv,max represents the installed capacity of each photovoltaic power station; SR(t) represents the actual solar radiation intensity in the tth period; SRstc represents the solar radiation intensity under standard test conditions; α p represents the power-temperature conversion coefficient of the solar cell module; T(t) represents the temperature of the solar cell module in the tth period; Tstc represents the air temperature under standard test conditions.

[0015] Preferably, the runoff process is represented by the output of the hydropower station, wherein the output factors of the hydropower station include the comprehensive efficiency of the hydropower station, the net head and the outflow flow; the outflow flow is the sum of the power generation reference flow and the abandoned water flow, and the net head is represented by a nonlinear function of the upstream and downstream water levels and the head loss; the calculation formula is as follows:

[0016] N h (t) = ηR(t)H(t);

[0017]

[0018] Where η represents the comprehensive efficiency coefficient of the hydropower station; R(t) represents the power generation flow in the tth period; H(t) represents the net water head in the tth period; WS(t) represents the abandoned water flow in the tth period; f vz represents the water level-reservoir capacity relationship curve; f qz It represents the tailwater level-flow relationship curve; It represents the average reservoir capacity in the tth period, that is, the average of the initial water storage in the tth period and the reservoir water storage at the end of the period; ΔH loss Indicates head loss.

[0019] Preferably, S2 comprises:

[0020] S21. Consider the minimum flow requirement of the hydropower station so that the minimum power generation output of the hydropower station is met;

[0021] S22. On the basis of satisfying S21, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy and does not generate photovoltaic power abandonment;

[0022] If the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station will store energy. If it exceeds the storage capacity of the pumped storage power station, the part exceeding the storage capacity of the pumped storage power station will be regarded as photovoltaic power abandonment, and the hydropower output process of the power generation area in the remaining period of the day will be adjusted. The hydropower station and the pumped storage station will adjust and compensate within the system transmission capacity, and the hydropower station and the pumped storage station will increase their output to meet the daily load demand.

[0023] As a preferred method, the energy storage calculation of the pumped storage power station is as follows:

[0024]

[0025] Where: Eph is the photovoltaic power absorbed by the pumped storage; Nph,max is the upper limit of the pumped storage output, Iph is the installed capacity of the pumped storage; Npv(t) is the photovoltaic output in the tth period; Nu is the upper limit of the transmission capacity of the power transmission channel;

[0026] The amount of photovoltaic power curtailment is calculated as follows:

[0027]

[0028] Where N h (t), N pv (t), N ph (t), are the hydropower output, photovoltaic output and pumped storage output in the t period respectively.

[0029] As a preferred embodiment, in S3: under different scenarios, the hydropower output, photovoltaic power abandonment rate and pumped storage photovoltaic ratio are calculated; the long-term photovoltaic power abandonment curve is fitted through the hydropower output and photovoltaic power abandonment rate sample points; the long-term pumped storage photovoltaic curve is fitted through the hydropower output and pumped storage photovoltaic ratio sample points; wherein the photovoltaic power abandonment rate refers to the ratio between the photovoltaic power abandonment amount and the total photovoltaic power amount within a day, and the specific photovoltaic power abandonment rate is specifically expressed as follows:

[0030]

[0031] Where: γ1 is the photovoltaic power abandonment rate; E c E is the amount of photovoltaic power wasted; pv is the total photovoltaic power;

[0032] The ratio of pumped storage to photovoltaic power is the ratio of pumped storage to total photovoltaic power. The specific expression of the ratio of pumped storage to photovoltaic power is as follows:

[0033]

[0034] In the formula, γ2 is the ratio of pumped storage to photovoltaic power. For photovoltaic grid connection, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy, that is, γ2 = 0; if the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station absorbs and stores the excess photovoltaic power.

[0035] Preferably, in S4, the objective function is expressed as:

[0036]

[0037] Where T is the number of monthly time periods; Nh represents the output of the hydropower station.

[0038] Preferably, N in the objective function pv (t) and N ph (t) are:

[0039] N pv (t) = P pv ·(1-f loss (N h (t))); N ph (t) = η ph ·P pv ·f ph (N h (t));

[0040] Where N h N is the online output of each cascade hydropower station in the tth period; pv P is the power output of each photovoltaic power station in the t period; pv Total photovoltaic power in period t; Nph Provide power to the pumped storage power station; ph is the comprehensive efficiency coefficient of the pumped storage power station, which is generally taken as 0.75; f loss is the long-term photovoltaic power abandonment curve; f ph Utilize the photovoltaic curve for long-term pumped storage.

[0041] Preferably, in S5, the complementary scheduling function is specifically expressed as follows:

[0042] N h =αAE+β;

[0043] Where AE is available energy, N h is the hydropower output in period t, and α and β are the coefficients of the complementary scheduling function.

[0044] Preferably, the available energy includes photovoltaic input energy, energy corresponding to the amount of water entering the reservoir during a period, and energy corresponding to the amount of water available at the beginning of the reservoir period. The available energy is specifically expressed as follows:

[0045] AE(t)=N pv (t)ΔT+KI(t)ΔTΔH(t)+K(V(t)-VU(t))ΔH'(t);

[0046] Where ΔT is the length of the scheduling period; N pv is the photovoltaic output; K is the output coefficient; ΔH and ΔH' are the heads corresponding to the net head and the reservoir water storage capacity respectively; I is the reservoir inflow; V is the initial reservoir water storage capacity in the tth period; VU is the dead storage capacity of the reservoir.

[0047] Beneficial effects of the present invention:

[0048] 1. This scheme focuses on the core issue of formulating a long-term dispatching strategy for the hydro-solar-storage complementary system. It simulates the long-term photovoltaic power abandonment function and long-term electricity price by upscaling the short-term model, considers the photovoltaic power abandonment in combination with short-term characteristics, and constructs a hydro-solar-storage complementary system model. It also deduces the complementary dispatching function with the power generation efficiency as the goal, and estimates the long-term pumped storage power generation. It aims to further improve the dispatching model of the hydro-solar-storage complementary system, maximize the utilization efficiency of renewable resources, provide a dispatching optimization method for the long-term and short-term coordination of hydro-solar-storage, and guide the operation of the hydro-solar-storage complementary system.

[0049] 2. This scheme simulates the hydropower-photovoltaic-storage complementary dispatching process based on the obtained dispatching function, runs in the test period, and evaluates and compares the obtained results with the conventional dispatching. Analyzing from the power generation evaluation index, the system power generation obtained by applying the dispatching function is better than the conventional dispatching. Compared with the conventional dispatching, the complementary dispatching function increases the hydropower generation and photovoltaic power generation by 899 million kWh (2.20%) and 4.26 kWh (0.98%) respectively. It shows that optimizing the dispatching through the dispatching function can make more effective use of water resources, thereby increasing the hydropower generation. At the same time, after applying the dispatching function, the dispatching flexibility of the hydropower station can better cooperate with the instability of photovoltaic power generation, thereby improving the utilization rate of photovoltaic power generation, which increases the online power generation of photovoltaic power generation, while the role of the pumped storage station is relatively weakened. In addition, the hydropower-photovoltaic-storage complementary system greatly weakens the abandoned power, and its abandoned power is reduced by 282 million kWh (-5.31%) compared with the conventional dispatching, further improving the utilization efficiency of energy, and increasing the overall system power generation by 11.81 kWh (1.30%). The dispatching function can improve the power generation of hydropower and photovoltaic power to a certain extent, which can serve as a reference for the dispatching and operation of the hydro-photovoltaic-storage complementary system. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Other features, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings. The drawings are only for the purpose of illustrating preferred embodiments and are not to be considered as limiting the present invention. Also, the same reference symbols are used throughout the drawings to represent the same parts.

[0051] Figure 1 is a flow chart of the method of the present invention;

[0052] Figure 2 It is a schematic diagram of the complementary scheduling function of the present invention;

[0053] Figure 3 It is the photovoltaic power abandonment rate function and the pumped storage photovoltaic function of the present invention. DETAILED DESCRIPTION

[0054] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0055] Example 1: Figure 1 As shown, a scheduling optimization method for long-term and short-term coordination of hydropower, photovoltaic and storage systems includes:

[0056] S1. Simulate short-term typical annual runoff process and photovoltaic process based on multiple scenarios.

[0057] Specifically, the photovoltaic process is represented by photovoltaic output, where the photovoltaic output calculation formula includes:

[0058]

[0059] Where: P pv,max represents the installed capacity of each photovoltaic power station; SR(t) represents the actual intensity of solar radiation in the tth period; SR stc Indicates the solar radiation intensity under standard test conditions, taking 1000W / m 2 ; α p represents the power-temperature conversion coefficient of the solar cell module, which is -0.35% / ℃; T(t) represents the temperature of the solar cell module in the tth period; T stc It indicates the air temperature under standard test conditions, which is 25℃.

[0060] Specifically, the runoff process is represented by the output of the hydropower station, where the output factors of the hydropower station include the comprehensive efficiency of the hydropower station, the net head and the outflow flow; the outflow flow is the sum of the power generation reference flow and the abandoned water flow, and the net head is represented by a nonlinear function of the upstream and downstream water levels and head losses; the calculation formula is as follows:

[0061] N h (t) = ηR(t)H(t);

[0062]

[0063] Where: η represents the comprehensive efficiency coefficient of the hydropower station, which is 9.81; R(t) represents the power generation flow in the tth period; H(t) represents the net water head in the tth period; WS(t) represents the abandoned water flow in the tth period; f vz (·) represents the water level-reservoir capacity relationship curve; f qz (·) represents the tailwater level-discharge relationship curve; It represents the average reservoir capacity in the tth period, that is, the average of the initial water storage in the tth period and the reservoir water storage at the end of the period; ΔH loss Indicates head loss.

[0064] S2. In real-time economic operation, the priority order of grid access is formulated according to the complementary relationship between water and light, and the complementary strategy of water, light and energy storage is determined.

[0065] Specifically, the S2 includes:

[0066] S21. Consider the minimum flow requirement of the hydropower station so that the minimum power generation output of the hydropower station is met;

[0067] S22. On the basis of satisfying S21, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy and does not generate photovoltaic power abandonment;

[0068] If the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station will store energy. If it exceeds the storage capacity of the pumped storage power station, the part exceeding the storage capacity of the pumped storage power station will be regarded as photovoltaic power abandonment, and the hydropower output process of the power generation area in the remaining period of the day will be adjusted. The hydropower station and the pumped storage station will adjust and compensate within the system transmission capacity, and the hydropower station and the pumped storage station will increase their output to meet the daily load demand.

[0069] Specifically, the energy storage calculation of the pumped storage power station is as follows:

[0070]

[0071] Where: E ph Pumped storage absorbs photovoltaic power; N ph,max is the upper limit of pumped storage output, I ph is the installed capacity of pumped storage; Npv(t) is the photovoltaic output in the tth period; N u It is the upper limit of the transmission capacity of the power transmission channel.

[0072] The amount of photovoltaic power curtailment is calculated as follows:

[0073]

[0074] Where N h (t), N pv (t), N ph (t), are the hydropower output, photovoltaic output and pumped storage output in the t period respectively.

[0075] S3. Consider multiple scenarios to simulate the short-term typical annual runoff process, photovoltaic process and hydro-PV-storage complementary strategy, and obtain the long-term photovoltaic power abandonment curve and the long-term pumped storage photovoltaic curve.

[0076] Specifically, in S3: under different scenarios, the hydropower output, photovoltaic power abandonment rate and pumped storage photovoltaic ratio are calculated; the long-term photovoltaic power abandonment curve is fitted through the hydropower output and photovoltaic power abandonment rate sample points; the long-term pumped storage photovoltaic curve is fitted through the hydropower output and pumped storage photovoltaic ratio sample points; among which, the photovoltaic power abandonment rate refers to the ratio between the photovoltaic power abandonment and the total photovoltaic power within a day, and the specific photovoltaic power abandonment rate is expressed as follows:

[0077] Where: γ1 is the photovoltaic power abandonment rate; E c E is the amount of photovoltaic power wasted; pv is the total photovoltaic power;

[0078] The ratio of pumped storage to photovoltaic power is the ratio of pumped storage to total photovoltaic power. The specific expression of the ratio of pumped storage to photovoltaic power is as follows:

[0079] In the formula, γ2 is the ratio of pumped storage to photovoltaic power. For photovoltaic grid connection, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy, that is, γ2 = 0; if the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station absorbs and stores the excess photovoltaic power.

[0080] Calculate the hydropower output, photovoltaic power abandonment rate and pumped storage photovoltaic ratio; fit the long-term photovoltaic power abandonment curve through the hydropower output and photovoltaic power abandonment rate sample points; fit the long-term pumped storage photovoltaic curve through the hydropower output and pumped storage photovoltaic ratio sample points.

[0081] It is understandable that under different scenarios, the daily PV power abandonment rate and the PV power utilization ratio of pumped storage are calculated on a daily basis, and the daily PV power abandonment rate and the PV power utilization ratio of pumped storage are obtained. Figure 3 The data points in daily units are connected to obtain the long-term photovoltaic power curtailment curve and the long-term pumped storage photovoltaic curve on a larger time scale (such as a month).

[0082] S4. Based on the long-term photovoltaic power curtailment curve and the long-term pumped storage photovoltaic curve, an objective function with the goal of maximizing power generation is constructed, and then combined with constraint conditions to construct a hydro-PV-storage complementary system model.

[0083] Specifically, in S4, the objective function is expressed as:

[0084] Where T is the number of monthly time periods; N h Indicates the output of the hydropower station.

[0085] Specifically, N in the objective function pv (t) and N ph (t) are:

[0086] N pv (t) = P pv ·(1-f loss (N h (t))); N ph (t) = η ph ·P pv ·f ph (N h (t));

[0087] Where N h N is the online output of each cascade hydropower station in the tth period; pvP is the power output of each photovoltaic power station in the t period; pv Total photovoltaic power in period t; N ph Provide power to the pumped storage power station; ph is the comprehensive efficiency coefficient of the pumped storage power station, which is generally taken as 0.75; f loss is the long-term photovoltaic power abandonment curve; f ph Utilize the photovoltaic curve for long-term pumped storage.

[0088] S5. Based on the hydro-solar-storage complementary system model, the discrete differential dynamic programming algorithm is used to solve the hydro-solar-storage complementary system model to obtain the medium- and long-term optimal scheduling samples. The available energy in the medium- and long-term optimal samples is used as the input variable, and the reservoir output is selected as the decision variable to fit the complementary scheduling function.

[0089] Specifically, in S5, the complementary scheduling function is specifically expressed as follows:

[0090] N h =αAE+β; where AE is the available energy, N h is the hydropower output in period t, and α and β are the coefficients of the complementary scheduling function.

[0091] Preferably, the available energy includes photovoltaic input energy, energy corresponding to the amount of water entering the reservoir during a period, and energy corresponding to the amount of water available at the beginning of the reservoir period. The available energy is specifically expressed as follows:

[0092] AE(t)=N pv (t)ΔT+KI(t)ΔTΔH(t)+K(V(t)-VU(t))ΔH'(t);

[0093] Where ΔT is the length of the scheduling period; N pv is the photovoltaic output; K is the output coefficient; ΔH and ΔH' are the heads corresponding to the net head and the reservoir water storage capacity respectively; I is the reservoir inflow; V is the initial reservoir water storage capacity in the tth period; VU is the dead storage capacity of the reservoir.

[0094] This embodiment focuses on the core issue of formulating a long-term scheduling strategy for the hydro-photovoltaic-storage complementary system, simulates the long-term photovoltaic power abandonment function and long-term electricity price by upscaling the short-term model, considers the photovoltaic power abandonment in combination with short-term characteristics, and constructs a hydro-photovoltaic-storage complementary system model. It also deduces the complementary scheduling function with the power generation efficiency as the goal, and estimates the long-term pumped storage power generation. It aims to further improve the scheduling model of the hydro-photovoltaic-storage complementary system, maximize the utilization efficiency of renewable resources, provide a scheduling optimization method for the long-term and short-term coordination of hydro-photovoltaic-storage, and guide the operation of the hydro-photovoltaic-storage complementary system.

[0095] Example 2: Taking a water-photovoltaic-storage complementary system consisting of a cascade hydropower station, a photovoltaic power station, and a pumped storage power station in a certain river basin as an example, the research period is from 1954 to 2020, and the rate is divided into a regular period (1954-2003) and a test period (1974-2020). Within a given scheduling period, according to the actual scheduling needs of the cascade hydropower station project, while considering the requirements of comprehensive utilization and other conditional constraints, the scheduling model takes the maximum power generation of the water-photovoltaic-storage complementary system as the objective function, and extracts the complementary scheduling function by combining the photovoltaic power abandonment function and the pumped storage photovoltaic function.

[0096] The obtained photovoltaic power abandonment curve and pumped storage photovoltaic power utilization curve are as follows: Figure 3 As shown in Table 1, they all show a trend of fluctuating downward first and then rising rapidly. The complementary scheduling function parameters are fitted through the medium- and long-term optimal scheduling samples, and the complementary scheduling function obtained is shown in Table 1.

[0097] Table 1 Complementary scheduling function parameters

[0098]

[0099]

[0100] Based on the obtained complementary scheduling function, the hydro-solar-storage complementary scheduling process is simulated and run during the test period. Figure 2 The results are shown in Table 1. The system power generation obtained by applying the complementary dispatch function is better than that of conventional dispatch. Compared with conventional dispatch, the complementary dispatch function increases the hydropower generation and photovoltaic power generation by 899 million kWh (2.20%) and 4.26 kWh (0.98%) respectively. It shows that optimizing the dispatch through the complementary dispatch function can make more effective use of water resources, thereby increasing the hydropower generation. At the same time, after applying the complementary dispatch function, the dispatch flexibility of the hydropower station can better cooperate with the instability of photovoltaic power generation, thereby improving the utilization rate of photovoltaic power generation, which increases the online power generation of photovoltaic power generation, while the role of the pumped storage station is relatively weakened. In addition, the hydro-photovoltaic storage complementary system greatly weakens the abandoned power, and its abandoned power is reduced by 282 million kWh (-5.31%) compared with conventional dispatch, further improving the utilization efficiency of energy, and increasing the overall system power generation by 11.81 kWh (1.30%). The complementary dispatch function has a certain improvement on the hydropower and photovoltaic power generation.

[0101] Table 1 Complementary scheduling function operation results

[0102]

[0103] The research method extracted a complementary scheduling function for long-term and short-term coordination, and considered the photovoltaic power curtailment and pumped storage power generation in combination with short-term characteristics, providing a reference for reservoir operation decisions.

[0104] The above specific embodiments are preferred embodiments of the present invention, and are not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to the present specific embodiments. All equivalent changes made in accordance with the shape, structure, and method of the present invention are within the protection scope of the present invention.

Claims

1. A scheduling optimization method for long-term and short-term coordination of hydropower, photovoltaic and energy storage, characterized in that: The steps include: S1. Simulate short-term typical annual runoff process and photovoltaic process based on multiple scenarios; S2. In real-time economic operation, the priority order of access to the grid is formulated according to the complementary relationship between water and light, and the complementary strategy between water, light and energy storage is determined; S3. Consider multiple scenarios to simulate the short-term typical annual runoff process, photovoltaic process and hydro-PV-storage complementary strategy, and obtain the long-term photovoltaic power abandonment curve and the long-term pumped storage photovoltaic curve; S4. Based on the long-term photovoltaic power abandonment curve and the long-term pumped storage photovoltaic curve, an objective function with the maximum power generation as the goal is constructed, and then combined with the constraint conditions to construct a water-solar-storage complementary system model; S5. Based on the hydro-solar-storage complementary system model, the discrete differential dynamic programming algorithm is used to solve the hydro-solar-storage complementary system model to obtain the medium- and long-term optimal scheduling samples. The available energy in the medium- and long-term optimal samples is used as the input variable, and the reservoir output is selected as the decision variable to fit the complementary scheduling function.

2. According to claim 1, a scheduling optimization method for long-term and short-term coordination of hydro-solar-energy storage is characterized by: The photovoltaic process is represented by photovoltaic output, wherein the photovoltaic output calculation formula includes: Where P pv,max represents the installed capacity of each photovoltaic power station; SR(t) represents the actual intensity of solar radiation in the tth period; SR stc Indicates the solar radiation intensity under standard test conditions; α p represents the power-temperature conversion coefficient of the solar cell module; T(t) represents the temperature of the solar cell module in the tth period; T stc Indicates the air temperature under standard test conditions.

3. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 1 is characterized by: The runoff process is represented by the output of the hydropower station, where the output factors of the hydropower station include the comprehensive efficiency of the hydropower station, the net head and the outflow flow; the outflow flow is the sum of the power generation flow and the abandoned water flow, and the net head is represented by a nonlinear function of the upstream and downstream water levels and head losses; the calculation formula is as follows: N h (t)=ηR(t)H(t); Where η represents the comprehensive efficiency coefficient of the hydropower station; R(t) represents the power generation flow in the tth period; H(t) represents the net water head in the tth period; WS(t) represents the abandoned water flow in the tth period; f vz represents the water level-reservoir capacity relationship curve; f qz It represents the tailwater level-flow relationship curve; It represents the average reservoir capacity in the tth period, that is, the average of the initial water storage in the tth period and the reservoir water storage at the end of the period; ΔH loss Indicates head loss.

4. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 1 is characterized in that: The S2 includes: S21. Consider the minimum flow requirement of the hydropower station so that the minimum power generation output of the hydropower station is met; S22. On the basis of satisfying S21, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy and does not generate photovoltaic power abandonment; If the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station will store energy. If it exceeds the storage capacity of the pumped storage power station, the part exceeding the storage capacity of the pumped storage power station will be regarded as photovoltaic power abandonment, and the hydropower output process of the power generation area in the remaining period of the day will be adjusted. The hydropower station and the pumped storage station will adjust and compensate within the system transmission capacity, and the hydropower station and the pumped storage station will increase their output to meet the daily load demand.

5. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 4 is characterized by: The energy storage calculation of the pumped storage power station is as follows: Where: E ph Pumped storage absorbs photovoltaic power; N ph,max is the upper limit of pumped storage output, I ph It is the installed capacity of pumped storage; N pv (t) is the photovoltaic output in the tth period; N u The upper limit of the transmission capacity of the power transmission channel; The amount of photovoltaic power curtailment is calculated as follows: Where N h (t), N pv (t), N ph (t), are the hydropower output, photovoltaic output and pumped storage output in the t period respectively.

6. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 1 is characterized in that: In S3: Under different scenarios, the hydropower output, photovoltaic power abandonment rate and pumped storage photovoltaic ratio are calculated; the long-term photovoltaic power abandonment curve is fitted through the hydropower output and photovoltaic power abandonment rate sample points; the long-term pumped storage photovoltaic curve is fitted through the hydropower output and pumped storage photovoltaic ratio sample points; among which, the photovoltaic power abandonment rate refers to the ratio between the photovoltaic power abandonment and the total photovoltaic power within a day. The specific photovoltaic power abandonment rate is expressed as follows: Where: γ1 is the photovoltaic power abandonment rate; E c E is the amount of photovoltaic power wasted; pv is the total photovoltaic power; The ratio of pumped storage to photovoltaic power is the ratio of pumped storage to total photovoltaic power. The specific expression of the ratio of pumped storage to photovoltaic power is as follows: In the formula, γ2 is the ratio of pumped storage to photovoltaic power. For photovoltaic grid connection, if the sum of the minimum power generation output and the photovoltaic output is less than or equal to the system transmission capacity, the pumped storage power station does not store energy, that is, γ2 = 0; if the sum of the minimum power generation output and the photovoltaic output is greater than the system transmission capacity, the pumped storage power station absorbs and stores the excess photovoltaic power.

7. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 1 is characterized in that: In S4, the objective function is expressed as: Where T is the number of monthly time periods; N h Indicates the output of the hydropower station.

8. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 7 is characterized in that: In the objective function, N pv (t) and N ph (t) are: N pv (t)=P pv ·(1-f loss (N h (t)));N ph (t)=η ph ·P pv ·f ph (N h (t)); Where N h N is the power output of each cascade hydropower station in the tth period; pv P is the power output of each photovoltaic power station in the t period; pv Total photovoltaic power in period t; N ph Provide power for the pumped storage power station to be connected to the grid; η ph is the comprehensive efficiency coefficient of the pumped storage power station, which is generally taken as 0.75; f loss is the long-term photovoltaic power abandonment curve; f ph Utilize the photovoltaic curve for long-term pumped storage.

9. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 1 is characterized in that: In S5, the complementary scheduling function is specifically expressed as follows: N h =αAE+β; Where AE is available energy, N h is the hydropower output in period t, and α and β are the coefficients of the complementary scheduling function.

10. The method for optimizing the scheduling of long-term and short-term coordination of hydro-solar-energy storage according to claim 9 is characterized in that: The available energy includes photovoltaic input energy, the energy corresponding to the amount of water entering the reservoir during the period, and the energy corresponding to the amount of water available at the beginning of the reservoir period. The available energy is specifically expressed as follows: AE(t)=N pv (t)ΔT+KI(t)ΔTΔH(t)+K(V(t)-VU(t))ΔH'(t); Where ΔT is the length of the scheduling period; N pv is the photovoltaic output; K is the output coefficient; ΔH and ΔH' are the heads corresponding to the net head and the reservoir water storage capacity respectively; I is the reservoir inflow; V is the initial reservoir water storage capacity in the tth period; VU is the dead storage capacity of the reservoir.

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