A medium- and long-term sequential production simulation method and system including a pumped storage power station

Abstract

The present invention discloses a medium- and long-term sequential production simulation method and system including a pumped-storage power station, including: obtaining the grid operation parameters in each optimization period in time sequence; determining the power generation of each power station in each optimization period based on the grid operation parameters and a pre-constructed sequential production simulation operation optimization model; determining the operation mode of each power station in the future medium- and long-term and formulating an annual / monthly power plan based on the power generation of each power station in each optimization period; the power station includes: a pumped-storage power station, a new energy power station and a thermal power unit; the sequential production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the power loss of pumped-storage motor water. The operation optimization model including new energy and pumped-storage power stations provided by the present invention takes into account the impact of the loss of pumped-storage power stations on the power generation of new energy, and improves the accuracy of the operation results.

Description

Technical Field

[0001] The present invention relates to the technical field of renewable energy power generation, and in particular to a medium- and long-term sequential production simulation method and system including a pumped-storage power station. Background Art

[0002] The randomness and intermittency of renewable energy output have brought great challenges to the planning and operation of power grids. With the rapid growth of renewable energy installed capacity, the phenomenon of renewable energy power abandonment has become more serious. Calculating the renewable energy consumption of provincial power grids in the future by means of renewable energy time series production simulation is an important technical means to determine the future annual operation mode of renewable energy, formulate annual / monthly electricity plans and promote renewable energy consumption. The main reasons for renewable energy power abandonment include two aspects: first, the startup capacity of thermal power units is too large. Due to the limitation of minimum technical output, the thermal power units that are started up more often occupy the power generation space of renewable energy; second, due to the strong random volatility of renewable energy output, when the renewable energy output is high, the system lacks the space to absorb it. Pumped-storage power stations are an effective technical means to improve the capacity of renewable energy consumption and reduce the abandonment of renewable energy. Their role in promoting renewable energy consumption is mainly reflected in two aspects: first, the pumped-storage power stations in the system have the function of peak power generation, which can reduce the startup mode of conventional units to meet peak loads, thereby reducing the minimum technical output of thermal power units in the system, making room for the absorption of renewable energy; second, during the abandonment period of renewable energy output peak, pumped-storage units can pump water to generate electricity, store the abandoned electricity, and generate electricity when the renewable energy output is low, thereby improving the level of renewable energy consumption. Therefore, establishing an operation optimization model of pumped-storage power stations suitable for time-series production simulation calculations is an important basis for realizing the promotion of renewable energy consumption by pumped-storage power stations.

[0003] However, the method provided in patent CN201410198715 - A method for optimizing the daily operation mode of a pumped-storage power station based on marginal power generation energy consumption is not applicable to the operation optimization problem of a power system containing large-scale new energy sources, because the principle for judging whether the pumped-storage power station performs pumping action in the patent is "from the perspective of system energy conservation and emission reduction, considering that the pumping energy consumption of the pumped-storage power station is equal to the power generation energy consumption of other thermal power units increased by supplying it with pumping water, when the pumping energy consumption of the pumped-storage power station is less than the power generation energy consumption of other units replaced by its power generation, it is considered that the operation of the pumped-storage power station is economical, environmentally friendly and in line with the peak-shaving operation optimization principle", so the technology in the patent cannot achieve the role of promoting the consumption of new energy.

[0004] Patent CN201611224474 - A method and device for optimizing the operation of renewable energy power generation in a multi-terminal flexible DC power grid. This patent provides a method and device for optimizing the operation of renewable energy power generation in a multi-terminal flexible DC power grid containing a pumped-storage power station. The objective function of this patent introduces line losses but does not introduce losses caused by pumping and releasing water from the pumped-storage power station.

[0005] Patent CN201710537648 - A pumped-storage power station combined with wind-solar complementary system and its optimization method. This patent provides a method and device for optimizing the operation of renewable energy power generation in a multi-terminal flexible DC power grid containing a pumped-storage power station. However, this patent does not consider the impact of the loss of water pumped and discharged from the pumped-storage power station on the renewable energy power generation.

[0006] Patent CN201910030590 - A control method for a wide-area power generation control system of a pumped-storage power station provides a control method for a pumped-storage power station participating in a power generation control system, but the patent does not consider the impact of water losses in the pumped-storage power station on the power generation of new energy.

[0007] Since the existing operation optimization models containing renewable energy and pumped storage power stations do not consider the impact of water loss in pumped storage power stations on renewable energy power generation, the obtained operation results may be contrary to the actual operation principles of the system. Summary of the invention

[0008] In order to solve the above-mentioned deficiencies in the prior art, the present invention provides a medium- and long-term sequential production simulation method including a pumped storage power station, comprising:

[0009] Obtain the power grid operation parameters in each optimization period in time sequence;

[0010] Based on the grid operation parameters and the pre-built time-series production simulation operation optimization model, determine the power generation status of each power station in each optimization period;

[0011] Based on the power generation of each power station in each optimized period, determine the operation mode of each power station in the future medium and long term and formulate annual / monthly power generation plans;

[0012] The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped and discharged by the pumped storage motor.

[0013] Preferably, the construction of the sequential production simulation operation optimization model includes:

[0014] An objective function is constructed with the goal of maximizing the difference between the power generation of renewable energy and the power loss of pumped water in the pumped storage power station during the entire optimization period, and constraint conditions are constructed for the objective function;

[0015] The constraints include: system power balance constraints, renewable energy power generation constraints, renewable energy power restriction constraints and pumped storage power station power generation constraints;

[0016] The power generation constraint of the pumped storage power station is constructed based on the state of power abandonment of new energy and the constraint that the pumped storage power station does not release water for power generation when power abandonment of new energy occurs.

[0017] Preferably, the objective function is as shown below:

[0018]

[0019] Where: obj: the difference between the renewable energy power generation and the pumped water power loss of the pumped storage power station in all optimization periods; T: the total number of optimization periods, t = 1, 2, ..., T; p w (t): renewable energy power generation at time t; p s (t): the power generation of the pumped storage power station at time t; p c (t): pumping power of the pumped storage power station at time t; Δt: the duration of each optimization period.

[0020] Preferably, the system power balance constraint is as shown in the following formula:

[0021]

[0022] Where: The power generation of the i-th thermal power unit at time t; I: the number of thermal power units in the entire network; p f (t): the power received by the interconnection line between the power grid and other regions at time t; p w (t): renewable energy power generation at time t; p s (t): the power generation of the pumped storage power station at time t; p c (t): pumping power of the pumped storage power station at time t; d(t): system load at time t; T: total number of optimization periods.

[0023] Preferably, the new energy power generation power constraint is as shown in the following formula:

[0024]

[0025] Where: p w (t): renewable energy power generation at time t; The theoretical maximum power generation of renewable energy at time t; T: the total number of optimization periods.

[0026] Preferably, the new energy power restriction constraint is as shown in the following formula:

[0027]

[0028] Where: W(t) is a 0-1 variable, indicating the state of renewable energy power abandonment at time t, W(t) = 1 indicates that renewable energy power abandonment occurs at time t, and W(t) = 0 indicates that renewable energy power abandonment does not occur at time t; m: constant; p w (t): renewable energy power generation at time t; The theoretical maximum power generation of renewable energy at time t; T: the total number of optimization periods.

[0029] Preferably, the power generation constraint of the pumped storage power station is as shown in the following formula:

[0030]

[0031] Where: x s (t) is a 0-1 variable, indicating the power generation state of the pumped storage power station at time t, x s (t) = 1 means that the pumped storage power station is in the power generation state at time t, s (t) = 0 means that the pumped storage power station is not in the power generation state at time t; p s : Minimum power generation capacity of the pumped storage power station; The maximum power generation capacity of the pumped storage power station; W(t) is a 0-1 variable, indicating the state of renewable energy abandonment at time t; T: the total number of optimization periods.

[0032] Preferably, the constraint conditions further include:

[0033] Pumped storage power station pumping power constraints, pumped storage power station storage capacity constraints, thermal power unit operation constraints and system interconnection line power transmission constraints.

[0034] Preferably, the power grid operation parameters include:

[0035] The maximum power generation capacity of renewable energy and the timing data of the whole network load during the optimization period, as well as the parameter data of pumped storage power stations, thermal power units and grid interconnection lines.

[0036] Preferably, the new energy power station includes: a wind turbine and a photovoltaic power station.

[0037] Based on the same inventive concept, the present invention also provides a medium- and long-term sequential production simulation system including a pumped storage power station, comprising:

[0038] An acquisition module is used to acquire the power grid operation parameters in each optimization period in time sequence;

[0039] A determination module, used to determine the power generation of each power station in each optimization period based on the power grid operation parameters and a pre-built time-series production simulation operation optimization model;

[0040] The planning module is used to determine the operation mode of each power station in the future medium and long term and formulate annual / monthly power plans based on the power generation of each power station in each optimized period;

[0041] The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped and discharged by the pumped storage motor.

[0042] Preferably, the system further comprises:

[0043] Construction module, used to build a time-series production simulation operation optimization model;

[0044] The building blocks include:

[0045] A construction unit, used to construct an objective function with the maximum difference between the power generation of renewable energy and the loss of pumped water power in the pumped storage power station during the entire optimization period as the goal, and also used to construct constraint conditions for the objective function;

[0046] The constraints include: system power balance constraints, renewable energy power generation constraints, renewable energy power restriction constraints and pumped storage power station power generation constraints;

[0047] The power generation constraint of the pumped storage power station is constructed based on the state of power abandonment of new energy and the constraint that the pumped storage power station does not release water for power generation when power abandonment of new energy occurs.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The technical solution provided by the present invention obtains the grid operation parameters within each optimization period; based on the grid operation parameters and a pre-constructed new energy time-series production simulation operation optimization model including a pumped-storage power station, the power generation conditions of the pumped-storage power station and other power sources within each optimization period, as well as the new energy consumption; based on the power generation conditions of the pumped-storage power station and other power sources at each moment within the optimization period, as well as the new energy consumption, the future medium- and long-term operation mode of the new energy is determined, the annual / monthly electricity plan is formulated, and the new energy consumption is promoted; wherein, the new energy time-series production simulation operation optimization model including the pumped-storage power station is constructed based on the power loss of pumped-storage motor water pumping and discharge and the state of new energy power abandonment, as well as the pumped-storage power station not discharging water for power generation when new energy power abandonment, and the operation optimization model including new energy and pumped-storage power station provided by the present invention takes into account the influence of the loss of water pumping and discharge of the pumped-storage power station on the power generation of new energy, thereby improving the accuracy of the operation results.

[0050] The technical solution provided by the present invention avoids the consumption of new energy by frequent pumping and discharging of water in the pumped-storage power station by adding a penalty for the power loss caused by pumping and discharging water in the objective function of the time-series production simulation operation optimization model.

[0051] The technical solution provided by the present invention adds a constraint that the pumped-storage power station does not release water for power generation when renewable energy is abandoned in the operation optimization model, and linearizes the constraint of not releasing water when power is abandoned by introducing a 0-1 integer variable, making the optimization model easy to solve and the production simulation results more consistent with the actual operation conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1It is a flow chart of a medium- and long-term sequential production simulation method including a pumped storage power station in the present invention;

[0053] Figure 2 It is a schematic diagram of the curve of the abandoned power of renewable energy, pumped storage pumping / discharging power and reservoir capacity in a week in an embodiment of the present invention;

[0054] Figure 3 It is a schematic diagram of the renewable energy power abandonment, pumped storage / discharge power, thermal power unit output and minimum output curve in a week in an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to better understand the present invention, the content of the present invention is further described below in conjunction with the accompanying drawings and examples.

[0056] Example 1

[0057] When constructing a simulation operation optimization model for the time-series production of new energy including a pumped-storage power station, the present invention needs to consider two factors: first, it is necessary to avoid the pumped-storage power station from increasing the amount of new energy consumption through frequent pumping and discharging actions. This is because the pumping and discharging efficiency ratio of the pumped-storage power station is about 75%, that is, when the pumping power consumption of the pumped-storage power station is 100MWh, its corresponding power generation is about 75MWh, and the remaining 25MWh of electricity is the loss of pumping and discharging, which can be regarded as "load" to some extent. Therefore, when the new energy time-series production simulation is carried out with the maximum power generation of new energy as the goal, it is necessary to limit the pumping state of the pumped-storage power station, otherwise the pumped-storage power station will increase the total load demand of the system through continuous pumping and discharging actions to achieve the role of absorbing new energy. Second, when new energy abandons power, the pumped-storage power station should avoid generating electricity to squeeze out the power generation space of new energy. However, the existing operation optimization models containing new energy and pumped-storage power stations do not consider the above two factors, so the obtained operation results will appear to be contrary to the actual operation principles of the system. The present invention achieves the above modeling objectives by introducing pumped storage losses into the optimization objective function, introducing additional 0-1 variables characterizing the power abandonment state of renewable energy into the constraint conditions, and the constraint that the pumped storage power station does not generate electricity under the power abandonment state.

[0058] like Figure 1 As shown, the present invention provides a medium- and long-term time-series production simulation method including a pumped storage power station, comprising:

[0059] Step S1, obtaining the power grid operation parameters in each optimization period in time sequence;

[0060] Step S2: determining the power generation of each power station in each optimization period based on the power grid operation parameters and the pre-built time-series production simulation operation optimization model;

[0061] Step S3: Based on the power generation of each power station in each optimized period, determine the operation mode of each power station in the future medium and long term and formulate an annual / monthly power plan;

[0062] The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped and discharged by the pumped storage motor.

[0063] The specific implementation process of the method of the present invention is as follows:

[0064] Step S1, obtaining the power grid operation parameters in each optimization period in time sequence, specifically including:

[0065] Obtain the theoretical maximum power generation of renewable energy and the time series data of the entire network load at all optimized moments, and obtain the parameter data of pumped storage power stations, thermal power units and grid tie lines;

[0066] Assume that the total number of optimization periods is T, t=1,2,...,T represents the tth period, obtain the theoretical maximum power generation power and the whole network load time series data of renewable energy at all optimization moments, and obtain the parameter data of pumped storage power station, thermal power unit and grid interconnection line.

[0067] Step S2: determining the power generation of each power station in each optimization period based on the power grid operation parameters and the pre-built time-series production simulation operation optimization model;

[0068] First, a simulation operation optimization model of renewable energy time-series production including pumped storage power stations is established, including:

[0069] (1) Objective function

[0070] The objective function is to maximize the difference between the renewable energy power generation and the pumped water power loss of the pumped storage power station during the entire optimization period. The mathematical expression is as follows:

[0071]

[0072] In the formula, p w (t) is the power generated by renewable energy at time t, p s (t) represents the power generation of the pumped storage power station at time t, p c (t) represents the pumping power of the pumped storage power station at time t, and Δt is the duration of each optimization period. The above objective function subtracts the pumping and discharging losses of the pumped storage power station. Therefore, under the action of maximizing the objective function, the model optimization result will try to avoid the power loss caused by the frequent pumping and discharging of the pumped storage power station, and can effectively eliminate the phenomenon that the pumped storage power station increases the consumption of new energy by frequent pumping and discharging.

[0073] (2) Constraints

[0074] The main constraints of the model are as follows:

[0075] 1) System power balance constraints

[0076]

[0077] In the above formula, is the power generation of the i-th thermal power unit at time t, I represents the number of thermal power units in the whole network, and p f (t) is the power received by the interconnection line between the power grid and other regions at time t, and d(t) is the system load at time t. This constraint means that at any time, the sum of the power generated by all power sources in the entire network and the power received by the interconnection line is equal to the load.

[0078] 2) Constraints on renewable energy power generation

[0079]

[0080] In the formula, is the theoretical maximum power generation capacity of the new energy at time t, which is the input data required for the time series production simulation calculation. This constraint indicates that the power generation capacity of the new energy at any time is not greater than its theoretical maximum power generation capacity.

[0081] 3) New energy power restriction constraints

[0082]

[0083] Wherein, W(t) is a 0-1 variable, indicating the state of power abandonment of new energy at time t, W(t) = 1 indicates that power abandonment of new energy occurs at time t, and W(t) = 0 indicates that power abandonment of new energy does not occur at time t. m is a sufficiently small constant.

[0084] 4) Power generation constraints of pumped storage power stations

[0085]

[0086] In the first constraint, x s (t) is a 0-1 variable, indicating the power generation state of the pumped storage power station at time t, x s (t) = 1 means that the pumped storage power station is in the power generation state at time t, s (t)=0 means that the pumped storage power station is not in the power generation state at time t. p s and They represent the minimum and maximum power generation of the pumped storage power station respectively.

[0087] The second constraint indicates that when renewable energy power is abandoned (W(t)=1), the pumped storage power station cannot generate electricity, which can avoid the phenomenon that renewable energy power is abandoned and the pumped storage power station generates electricity, occupying the renewable energy power generation space.

[0088] In addition to the above constraints, this model also includes pumped power constraints of pumped storage power stations, storage capacity constraints of pumped storage power stations, operation constraints of thermal power units, and power transmission constraints of system interconnection lines, which are not described in detail one by one in the present invention.

[0089] In summary, the above optimization objectives and constraints constitute the simulation operation optimization model of new energy sequential production including pumped storage power stations, which is a mixed integer linear programming model.

[0090] The commercial optimization software Cplex is then called to solve the optimization model to obtain the power generation of the pumped-storage power station and other power stations at each moment, as well as the amount of new energy consumed.

[0091] Step S3: Based on the power generation of each power station in each optimized period, determine the operation mode of each power station in the future medium and long term and formulate an annual / monthly power plan.

[0092] This embodiment uses a regional power grid as an example to carry out testing, with an optimization duration of 4 weeks and a time resolution of 1 hour. The installed capacity of wind power in the entire network is 12770MW, and the installed capacity of photovoltaic power generation is 6940MW. The power grid contains 1 pumped storage power station, equipped with 4 200MW units, with a maximum pumping and discharge power of 800MW, and a full storage capacity of 6000MWh. According to production simulation calculations, the wind power abandonment rate of the entire network is 4.18%, and the photovoltaic abandonment rate is 3.12%.

[0093] Figure 2 The curves of renewable energy power curtailment, pumped storage pumping / discharging power and reservoir capacity for 168 hours in a week are displayed. It can be found that the regulation of the pumped storage power station effectively reduces renewable energy power curtailment, and the pumped storage power station is pumping water at full power when renewable energy power curtailment occurs, indicating that the regulation capacity of the pumped storage has been maximized when power curtailment occurs.

[0094] Figure 3 The curves of abandoned renewable energy power, pumped storage pumping / discharging power, thermal power unit output and minimum output in a certain week are displayed. It can be found that when the pumped storage power station is pumping water, the output of the thermal power unit has reached the minimum technical output level. When the output of the thermal power unit is higher than the minimum technical output, the pumped storage power station does not pump water, which means that the pumped storage power station has not absorbed new energy through too frequent pumping and discharging actions.

[0095] In addition, by Figure 3 It can be seen that from time 67 to 72, the output of the thermal power unit reached the minimum technical output level, and the pumped storage power station also generated electricity, which shows that the pumped storage power station achieved the role of peak power generation. The above results verify the effectiveness of the method proposed in the present invention.

[0096] The method provided in patent CN201410198715 is not applicable to the operation optimization problem of power systems containing large-scale renewable energy, because compared with thermal power, renewable energy is clean energy and can be considered to have no power generation energy consumption. Therefore, in the concept of this application, when renewable energy is abandoned, the pumped storage power station will not pump water, and its energy consumption is definitely higher than that of renewable energy power generation, thus achieving the effect of promoting the consumption of new energy.

[0097] Example 2

[0098] Based on the same inventive concept, an embodiment of the present invention further provides a medium- and long-term sequential production simulation system including a pumped storage power station, comprising:

[0099] An acquisition module is used to acquire the power grid operation parameters in each optimization period in time sequence;

[0100] A determination module, used to determine the power generation of each power station in each optimization period based on the power grid operation parameters and a pre-built time-series production simulation operation optimization model;

[0101] The planning module is used to determine the operation mode of each power station in the future medium and long term and formulate annual / monthly power plans based on the power generation of each power station in each optimized period;

[0102] The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped and discharged by the pumped storage motor.

[0103] In an embodiment, the system further comprises:

[0104] Construction module, used to build a time-series production simulation operation optimization model;

[0105] The building blocks include:

[0106] A construction unit, used to construct an objective function with the maximum difference between the power generation of renewable energy and the loss of pumped water power in the pumped storage power station during the entire optimization period as the goal, and also used to construct constraint conditions for the objective function;

[0107] The constraints include: system power balance constraints, renewable energy power generation constraints, renewable energy power restriction constraints and pumped storage power station power generation constraints;

[0108] The power generation constraint of the pumped storage power station is constructed based on the state of power abandonment of new energy and the constraint that the pumped storage power station does not release water for power generation when power abandonment of new energy occurs.

[0109] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0110] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A medium- and long-term sequential production simulation method including a pumped storage power station, characterized in that: include: Obtain the power grid operation parameters in each optimization period in time sequence; Based on the grid operation parameters and the pre-built time-series production simulation operation optimization model, determine the power generation status of each power station in each optimization period; Based on the power generation of each power station in each optimized period, determine the operation mode of each power station in the future medium and long term and formulate annual / monthly power generation plans; The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped by the pumped storage motor; The construction of the sequential production simulation operation optimization model includes: An objective function is constructed with the goal of maximizing the difference between the power generation of renewable energy and the power loss of pumped water in the pumped storage power station during the entire optimization period, and constraint conditions are constructed for the objective function; The constraints include: system power balance constraints, renewable energy power generation constraints, renewable energy power restriction constraints and pumped storage power station power generation constraints; The power generation constraint of the pumped storage power station is constructed based on the state of power abandonment of new energy and the constraint that the pumped storage power station does not release water for power generation when power abandonment of new energy occurs; The objective function is shown in the following formula: Where: obj: the difference between the renewable energy power generation and the pumped water power loss of the pumped storage power station in all optimization periods; T: the total number of optimization periods, t = 1, 2, ..., T; p w (t): renewable energy power generation at time t; p s (t): the power generation of the pumped storage power station at time t; p c (t): pumping power of the pumped storage power station at time t; Δt: the duration of each optimization period.

2. The method according to claim 1, characterized in that The system power balance constraint is shown in the following formula: Where: The power generation of the i-th thermal power unit at time t; I: number of thermal power generating units in the whole network; p f (t): the power received by the interconnection line between the power grid and other regions at time t; p w (t): renewable energy power generation at time t; p s (t): the power generation of the pumped storage power station at time t; p c (t): pumping power of the pumped storage power station at time t; d(t): system load at time t; T: total number of optimization periods.

3. The method according to claim 1, characterized in that The new energy power generation power constraint is as follows: Where: p w (t): renewable energy power generation at time t; The theoretical maximum power generation of new energy at time t; T: total number of optimization periods.

4. The method according to claim 1, characterized in that The new energy power restriction constraint is as follows: Where: W(t) is a 0-1 variable, indicating the state of power abandonment of new energy at time t. W(t) = 1 indicates that power abandonment of new energy occurs at time t, and W(t) = 0 indicates that power abandonment of new energy does not occur at time t. m: constant; p w (t): renewable energy power generation at time t; The theoretical maximum power generation of new energy at time t; T: total number of optimization periods.

5. The method according to claim 1, characterized in that The power generation constraint of the pumped storage power station is as follows: Where: x s (t) is a 0-1 variable, indicating the power generation state of the pumped storage power station at time t, x s (t) = 1 means that the pumped storage power station is in the power generation state at time t, s (t) = 0 means that the pumped storage power station is not in the power generation state at time t; s : Minimum power generation capacity of the pumped storage power station; The maximum power generation of the pumped storage power station; W(t) is a 0-1 variable, indicating the state of renewable energy abandonment at time t; T: total number of optimization periods.

6. The method according to claim 1, characterized in that The constraints also include: Pumped storage power station pumping power constraints, pumped storage power station storage capacity constraints, thermal power unit operation constraints and system interconnection line power transmission constraints.

7. The method according to claim 1, characterized in that The power grid operation parameters include: The maximum power generation capacity of renewable energy and the timing data of the whole network load during the optimization period, as well as the parameter data of pumped storage power stations, thermal power units and grid interconnection lines.

8. The method according to claim 1, characterized in that The new energy power station includes: a wind turbine and a photovoltaic power station.

9. A medium- and long-term sequential production simulation system including a pumped storage power station, characterized in that: include: An acquisition module is used to acquire the power grid operation parameters in each optimization period in time sequence; A determination module, used to determine the power generation of each power station in each optimization period based on the power grid operation parameters and a pre-built time-series production simulation operation optimization model; The planning module is used to determine the operation mode of each power station in the future medium and long term and formulate annual / monthly power plans based on the power generation of each power station in each optimized period; The power station includes: a pumped storage power station, a new energy power station and a thermal power unit; the time-series production simulation operation optimization model is constructed with the goal of maximizing the utilization of new energy and combining the loss of water and electricity pumped by the pumped storage motor; The system further comprises: Construction module, used to build a time-series production simulation operation optimization model; The building blocks include: A construction unit, used to construct an objective function with the maximum difference between the power generation of renewable energy and the loss of pumped water power in the pumped storage power station during the entire optimization period as the goal, and also used to construct constraint conditions for the objective function; The constraints include: system power balance constraints, renewable energy power generation constraints, renewable energy power restriction constraints and pumped storage power station power generation constraints; The power generation constraint of the pumped storage power station is constructed based on the state of power abandonment of new energy and the constraint that the pumped storage power station does not release water for power generation when power abandonment of new energy occurs; The objective function is shown in the following formula: Where: obj: the difference between the renewable energy power generation and the pumped water power loss of the pumped storage power station in all optimization periods; T: the total number of optimization periods, t = 1, 2, ..., T; p w (t): renewable energy power generation at time t; p s (t): the power generation of the pumped storage power station at time t; p c (t): pumping power of the pumped storage power station at time t; Δt: the duration of each optimization period.

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