Cascade hydropower integration transformation and net rack planning cooperation method for improving system flexibility

Abstract

The invention discloses a cascade hydropower integration transformation and net rack planning cooperation method for improving system flexibility, and provides a typical scene generation method based on an improved generative adversarial network and a K-means clustering method, which is used for providing a typical scene set for cascade hydropower integration transformation and a line extension configuration model. A cascade hydropower fusion transformation and line expansion double-layer optimization model oriented to system flexibility improvement is established, and comprises an upper-layer configuration model based on multi-target whale algorithm solution and a lower-layer operation model based on a McCormick convex envelope relaxation method. And finally, solving the double-layer model to obtain a cascade hydropower fusion transformation and line expansion configuration scheme. According to the method, the mutual influence of flexibility and economy is comprehensively considered, and flexible effective utilization is provided for cascade hydropower integration transformation.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and in particular to a method for coordinating cascade hydropower integration transformation and grid planning for improving system flexibility. Background Art

[0002] The proportion of renewable energy in the power system is increasing day by day. The seasonal, random and intermittent fluctuations of renewable energy power generation have led to severe challenges in the flexibility demand of new power systems on multiple time scales such as days, months, seasons and years. The integration and transformation of existing cascade hydropower stations and the construction of pumped-storage units to form cascade hybrid pumped-storage hydropower stations will promote the gradual transformation of conventional hydropower from "power supplier" to "power supplier + flexible regulator", which is of great significance to meet the flexibility demands of renewable energy output and load fluctuations and build a new power system with renewable energy as the main body.

[0003] The effective utilization of the flexibility provided by cascade hydropower integration transformation is limited by the transmission carrying capacity of the transmission channel. Existing research on cascade hydropower integration transformation rarely considers the situation where the flexibility provided by cascade hydropower integration transformation is not effectively utilized due to insufficient carrying capacity of the transmission channel. Summary of the invention

[0004] The purpose of the present invention is to overcome the problem of not considering flexibility in the prior art, and to provide a method for coordinating cascade hydropower integration transformation and grid planning to enhance system flexibility.

[0005] To achieve the above objectives, the technical solution of the present invention is:

[0006] In the first aspect, the present invention proposes a method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility, comprising:

[0007] S1. Generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand, and obtain a typical scenario set;

[0008] S2. Based on the obtained typical scenario set and the flexibility evaluation index of the power system, a two-layer optimization configuration model for improving system flexibility is established, including an upper-layer cascade hydropower integration transformation and grid planning model and a lower-layer operation model;

[0009] S3. The multi-objective whale algorithm and Gurobi solver are used to solve the above two-layer optimization configuration model to obtain the system cascade hydropower integration transformation and grid planning scheme.

[0010] The S1 includes: S11, establishing an improved generative adversarial network model with gradient penalty for the characteristics of the new energy output and the load demand respectively; the dimension of the improved generative adversarial network model with gradient penalty is consistent with the data dimension of the new energy output and the load demand, and can learn the data distribution characteristics of the new energy output and the load demand;

[0011] S12, randomly selecting 80% of the new energy output data and load demand data as training data, and the rest as test data, and inputting the training data into the constructed generative adversarial network model for training;

[0012] S13, after the training is completed, extract the generator in the trained network, use the noise data that obeys the normal distribution as input, and generate the scenario sets of new energy output and load demand respectively;

[0013] S14. Use the K-means clustering method to cluster the generated renewable energy output and load demand scenarios respectively, obtain several typical renewable energy output and load demand scenarios, and combine the two to obtain a typical scenario set Γ.

[0014] In S2, the flexibility evaluation index of the power system includes: a system node flexibility evaluation index and a system network flexibility evaluation index;

[0015] The calculation formula of the system node flexibility evaluation index is as follows:

[0016]

[0017] In the above formula, F node,s is the node flexibility index of the system under the typical scenario s, T is the flexibility evaluation time period, and F node,s,t is the node flexibility index at time t in a typical scenario s, are the upper and lower adjustment point flexibility indicators of the system at time t in a typical scenario s, They are the upward and downward flexibility requirements of the system at time t in a typical scenario s, They are the upward and downward flexibility supply of the system at time t under the typical scenario s;

[0018] Said It is calculated using the following formula:

[0019]

[0020] In the above formula, are the maximum and minimum controllable power requirements of the system at time t+1 under typical scenario s, are the maximum and minimum controllable power requirements of the system at time t under typical scenario s, They are the upward and downward flexibility supply of thermal power units at time t under typical scenario s, They are the upward and downward flexibility supply of hydropower units at time t under typical scenario s, They are respectively the upward and downward flexibility supply of the pumped storage unit at time t under the typical scenario s; It is calculated using the following formula:

[0021]

[0022]

[0023] In the above formula, N th is the number of thermal power units in the system, γ th,g,s,t , P th,g,s,t are the start / stop status and output power of thermal power unit g at time t under typical scenario s, P th,g,max , P th,g,min are the upper and lower limits of the output of thermal power unit g, are the upward and downward climbing rates of thermal power unit g, Δt is the scheduling time interval, I is the number of hydropower stations, N i is the number of hydropower units in hydropower station i, u i,n,s,t、 P i,n,s,t is the start / stop status and output of the nth unit of hydropower station i in period t under typical scenario s, P i,n are the upper and lower limits of the output of the nth unit of hydropower station i, are the upward and downward climbing rates of the nth unit of hydropower station i, N pum,i is the number of pumped storage units in hydropower station i, P vp,i,m,s,t、 P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,max,i,m、 P vg,max,i,m are the maximum pumping power and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. are the upward and downward climbing rates of the mth pumped storage unit of hydropower station i respectively; the calculation formula of the system network transmission flexibility evaluation index is as follows:

[0024]

[0025] F s,j,u =A s,j,u +λB s,j,u ; F s,j,d =A s,j,d +λB s,j,d ;

[0026] In the above formula, Fnet,s is the network transmission flexibility index in the system time period T under the typical scenario s, N is the number of lines, and F net,s,j is the network transmission flexibility index of line j in time period T under typical scenario s, s,j,u 、F s,j,d are the comprehensive indicators of insufficient flexibility of upward and downward adjustment of line j, A s,j,u , A s,j,d are the average insufficient flexibility load for upward and downward adjustment of line j, λ is the weight factor, B s,j,u , B s,j,d are the discrete degrees of insufficient flexibility carrying capacity for upward and downward adjustment of line j respectively; s,j,u , A s,j,d , B s,j,u , B s,j,d It is calculated using the following formula:

[0027]

[0028] In the above formula, G s,j,u,t , G s,j,d,t are the transmission margins of up and down line flexibility of line j at time t in typical scenario s, T s,j,u 、T s,j,d are the sum of the periods of insufficient upward and downward flexibility of line j in typical scenario s; s,j,u,t , G s,j,d,t It is calculated using the following formula:

[0029]

[0030] In the above formula, P max,j is the maximum permissible transmission capacity of line j, P s,j,t is the transmission power value of line j at time t in typical scenario s, are the allocation of upward and downward flexibility demands of the system at time t on line j under typical scenario s, are respectively the allocation of upward and downward flexibility supply of the system at time t on line j under typical scenario s; The following calculation formula is used:

[0031]

[0032] In the above formula, M is the number of nodes in the system, is the power transmission distribution factor of node k’s injected power to line j in typical scenario s, are the upward and downward flexibility requirements of node k at time t in a typical scenario s, They are respectively the upward and downward flexibility supply of node k at time t in the typical scenario s.

[0033] In S2, the objective function of the upper cascade hydropower integration transformation and grid planning model is:

[0034] f 1 =min{C total ,F′ node ,F′ net};

[0035]

[0036] In the above formula, C total is the total annual cost of the power system, F′ node , F′ net are the node and network transmission flexibility evaluation indicators of the system, C con is the equivalent annual construction and maintenance cost, is the probability of a typical scene s appearing, C oper,s is the annual operating cost under the typical scenario s, F node,s 、F net,s are the node and network transmission flexibility evaluation indicators under typical scenario s, respectively, and Γ is the set of typical scenarios;

[0037] The objective function of the lower-level running model is:

[0038]

[0039] In the above formula, C G,s , are the annual power generation cost, annual penalty cost for abandoning new energy, and annual penalty cost for load shedding of the system under the typical scenario s, respectively. g 、b g 、c g are the power generation cost coefficients of thermal power unit g, P th,g,s,t is the output power of thermal power unit g under typical scenario s at time t, c re 、c load They are the penalty cost coefficient for abandoning new energy and the penalty cost coefficient for load shedding, P re,k,s,t are the maximum output power and actual absorption power of the new energy of node k in the typical scenario s at time t, P load,k,s,t are the power supply required and actual power supply of node k in typical scenario s at time t, G th , G re , Π are controllable power supply units, new energy, and system node collection respectively.

[0040] The constraints of the upper-level planning model include pumped storage units and line planning and construction constraints, including:

[0041]

[0042] In the above formula, x i The number of pumped storage units added at the hydropower station i, are the upper and lower limits of the number of additional pumped storage units to be built at hydropower station i, l j is the number of newly built lines j, are the upper and lower limits of the number of newly built lines j, is the equivalent annual construction and maintenance cost cap, Π 1 A collection of hydropower stations to be built with pumped storage units. 2 is a collection of lines to be built;

[0043] The constraints of the lower-level operation model include: power flow balance constraints, line capacity constraints, thermal power output constraints, hydropower output constraints, pumped storage operation constraints, and node voltage phase angle constraints. The formula is as follows:

[0044] a. Power flow balance constraints:

[0045] In the above formula, P th,s , P hy,s , P re,s , P load,s They are the output vector of thermal power units, the output vector of hydropower units, the output vector of new energy units, and the node load vector under the typical scenario s. are respectively the pumped storage power generation and pumped hydropower vectors, B is the node admittance matrix, θ s is the node voltage phase angle vector under typical scenario s;

[0046] b. Line capacity constraints:

[0047] In the above formula, is the number of line j before expansion, P′ j,max is the transmission capacity of a single line j;

[0048] c. Thermal power output constraints

[0049] d. Hydropower output constraints include hydropower station constraints and hydropower unit constraints;

[0050] d1. Hydropower station constraints include hydraulic connection constraints, water level constraints, outflow constraints, hydropower station output constraints, water level-reservoir capacity relationship constraints, and tailwater level-discharge relationship constraints:

[0051] Hydraulic connection constraint: V i,s,t=V i,s,t-1 +3600(I i,s,t -Q i,s,t )Δt;

[0052]

[0053]

[0054] Water level constraints:

[0055] Outbound traffic constraints:

[0056] Hydropower station output constraints:

[0057] Water level-reservoir capacity relationship constraints:

[0058] Tailwater level-discharge relationship constraints:

[0059] In the above formula, V i,s,t is the storage capacity of hydropower station i in period t under typical scenario s, I i,s,t is the inflow of hydropower station i in period t under typical scenario s, Q i,s,t is the outflow of hydropower station i in period t under typical scenario s, τ is the water lag time between hydropower station i and its upstream hydropower station i-1, Q i-1,s,t-τ is the outflow of hydropower station i-1 in period t-τ after considering water lag under typical scenario s; R i,s,t is the interval flow between hydropower station i-1 and hydropower station i in period t under typical scenario s, are the pumping and power generation flows of the pumped storage unit i in the typical scenario s, are respectively the power generation and abandoned water flow of hydropower station i in period t under typical scenario s, is the water level in front of the dam of hydropower station i in the reservoir at time period t under typical scenario s, are the upper and lower limits of the water level in front of the dam of the hydropower station i in the reservoir where it is located, is the initial water level during the scheduling period under the typical scenario s, Q i are the upper and lower limits of the outflow flow of hydropower station i, is the output of hydropower station i in period t under typical scenario s, P i hydro are the upper and lower limits of the output of hydropower station i, respectively, and f i zv (·) is the nonlinear relationship curve function between water level and storage capacity of the reservoir where the hydropower station i is located, fi zq (·) is the nonlinear relationship curve function between the tailwater level and discharge flow of hydropower station i, is the tailwater level of hydropower station i in period t under typical scenario s;

[0060] d2. Hydropower unit constraints include: unit output constraints, unit power flow constraints, unit start-up and shutdown duration constraints, unit output ramp constraints, unit power head constraints, and unit power characteristic constraints:

[0061] Unit output constraints:

[0062] Unit power generation flow constraints:

[0063] Unit start-up and shutdown duration constraints:

[0064] Unit output ramp constraint: -ΔP i,n ≤P i,n,s,t+1 -P i,n,s,t ≤ΔP i,n ;

[0065] Unit generating head constraints:

[0066] Unit power characteristic constraints:

[0067] In the above formula, u i,n,s,t is the start-up and shutdown state variable of the nth unit of hydropower station i in period t under typical scenario s, u i,n,s,t ∈{0,1};P i,n,s,t is the output of the nth unit of hydropower station i in period t under typical scenario s; P i ,n are the upper and lower limits of the output of the nth unit of the hydropower station i, 1 represents the start state, and 0 represents the shutdown state; N i is the total number of units included in hydropower station i; is the power generation flow of the nth unit of hydropower station i in period t under typical scenario s, are the upper and lower limits of the power generation flow of the nth unit of hydropower station i, respectively; are the startup and shutdown operation variables of the nth unit of hydropower station i in period t under typical scenario s; are the minimum startup and shutdown durations of the nth unit of hydropower station i, respectively; is the maximum number of startup times of the nth unit of hydropower station i during the dispatch period; ΔP i,n is the climbing capacity of the nth unit of the hydropower station i; H i,n,s,tis the generating head of the nth unit of hydropower station i in period t under typical scenario s; is the nonlinear relationship function of output-head-flow of the nth unit of hydropower station i;

[0068] e. The pumped storage operation constraints: x vp,i,m,s,t +x vg,i,m,s,t ≤1;

[0069] P vp,min x vp,i,m,s,t ≤P vp,i,m,s,t ≤P vp,max x vp,i,m,s,t ;

[0070] P vg,min x vg,i,m,s,t ≤P vg,i,m,s,t ≤P vg,max x vg,i,m,s,t ;

[0071]

[0072] In the above formula, x vp,i,m,s,t 、x vg,i,m,s,t are the pumping and power generation states of the mth pumped storage unit of hydropower station i in the typical scenario s in time period t. When the value is 1, it means it is in this state, and when the value is 0, it means it is not in this state. vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,min,i,m , P vp,max,i,m , P vg,min,i,m , P vg,max,i,m are the minimum pumping power, maximum pumping power, minimum generating power, and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. vp,i,m,s,t , Q vg,i,m,s,t are the pumping and power generation flows of the mth pumped-storage unit of hydropower station i in period t under typical scenario s, η p , η g are the pumping and power generation efficiencies of a single pumped storage unit, ρ 0 , g are the average density of water and the acceleration due to gravity, h i,s is the average water head of hydropower station i under typical scenario s, N pum,i is the number of pumped storage units in hydropower station i;

[0073] f. Node voltage phase angle constraint:

[0074] In the above formula, θ k,s,t is the voltage phase angle of node k in period t under typical scenario s, They are the upper and lower limits of the voltage phase angle at node k respectively.

[0075] In S3, the specific operation method for solving the two-layer optimization model includes:

[0076] S31, nonlinear equation constraints of the linearized inner model, including water level-storage capacity relationship constraints, tailwater level-discharge relationship constraints, and unit dynamic characteristics constraints;

[0077] S32, initializing the parameters of the multi-objective whale algorithm, including the population number of the algorithm, the maximum number of iterations, and the random pumped storage expansion and line configuration initial plan;

[0078] S33, bringing the initial plan of pumped storage expansion and line configuration into the linearized lower model, calling the Gurobi mathematical solver to solve the lower model for the generated typical scenario, and passing the obtained system flow data to the upper model;

[0079] S34. Calculate the objective function value of the upper model for the generated typical scenario and the flow data transmitted by the lower model, solve the upper model using the multi-objective whale algorithm, and obtain the pumped storage expansion and line configuration plan;

[0080] S35. Determine whether the maximum number of iterations has been reached. If so, output the pumped storage expansion and line configuration plan. Otherwise, update the pumped storage expansion and line configuration plan and repeat steps S33-S35.

[0081] The nonlinear equation water level-storage capacity relationship constraint of the linearized inner layer model is obtained:

[0082]

[0083] In the above formula, V i n is the nth interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity; is the n-1th interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity; is an indicator variable. When the water level in front of the dam of the reservoir where the hydropower station i is located in the typical scenario s is in the nth interval in time period t, otherwise, is the water level in front of the dam of hydropower station i in the nth interval under the typical scenario s;

[0084] The nonlinear equation of the tailwater level-discharge relationship constraint of the linearized inner layer model is obtained:

[0085]

[0086] In the above formula, is the nth interpolation point of the outflow of hydropower station i and its corresponding tailwater level; is the n-1th interpolation point of the outflow of hydropower station i and its corresponding tailwater level; is an indicator variable. When the outflow of hydropower station i in period t under typical scenario s is in the nth interval, otherwise, is the outflow of hydropower station i in the nth interval under typical scenario s;

[0087] The specific operation method of the nonlinear equation unit dynamic characteristic constraint of the linearized inner model includes:

[0088] The unit dynamic characteristic constraints are transformed into the following form using McCormick convex envelope relaxation method to complete the linearization of the nonlinear unit dynamic characteristic constraints:

[0089]

[0090] In the above formula, η i,n is the power generation efficiency of the nth unit of hydropower station i, They are the upper and lower limits of the generating head of the nth unit of hydropower station i.

[0091] In the second aspect, the present invention proposes a cascade hydropower integration transformation and grid planning coordination system for improving system flexibility, including: a typical scenario set generation module, a two-layer optimization configuration model construction module, and a model solving module;

[0092] Typical scenario set generation module: used to generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand, and obtain typical scenario sets;

[0093] Two-layer optimization configuration model building module: used to establish a two-layer optimization configuration model to improve system flexibility based on the obtained typical scenario set and the flexibility evaluation index of the power system, including the upper-layer cascade hydropower integration transformation and grid planning model and the lower-layer operation model;

[0094] Model solving module: It is used to solve the above two-layer optimization configuration model using the multi-objective whale algorithm and Gurobi solver to obtain the system cascade hydropower integration transformation and grid planning scheme.

[0095] Compared with the prior art, the present invention has the following beneficial effects:

[0096] 1. In the collaborative method of cascade hydropower integration transformation and grid planning for improving system flexibility, the present invention adopts random scenario generation and K-means-based scenario reduction method to generate typical scenarios, which can provide targeted typical scenarios for optimal configuration, thereby converting the uncertainty problem after renewable energy is connected to the power system into a random optimization problem.

[0097] 2. The present invention provides a coordinated method for cascade hydropower integration and transformation and grid planning to enhance system flexibility, which coordinates the integration and transformation of cascade hydropower and the expansion planning of transmission lines, fully considers the impact of line transmission channels on the effective use of the flexibility provided by the integration and transformation of cascade hydropower, effectively taps the line transmission potential, and significantly improves system flexibility.

[0098] 3. In the collaborative method of cascade hydropower integration transformation and grid planning for improving system flexibility, the present invention establishes a two-layer optimization model of a lower-layer operation model and an upper-layer pumped storage and line configuration, introduces system node flexibility evaluation indicators and system network transmission flexibility evaluation indicators, effectively coordinates the resource allocation stage and the system operation stage, comprehensively considers the mutual influence of flexibility and economy, and ensures the improvement of power grid flexibility and economy.

[0099] 4. In the collaborative method of cascade hydropower integration transformation and grid planning for improving system flexibility, the multi-objective whale algorithm is used to solve the upper-level planning model, which can achieve the goal of fast convergence speed while maintaining population diversity; at the same time, the constraint linearization of the lower-level model is performed using piecewise linearization and McCormick convex envelope relaxation method, which can convert the lower-level model into a MILP model, reducing the difficulty of solving. The more mature Gurobi solver can be called through MATLAB's YALMIP toolbox to quickly solve the problem. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] Figure 1 This is an algorithm structure diagram of the present invention.

[0101] Figure 2 This is a workflow diagram for the joint solution of the upper and lower layer algorithms of the present invention.

[0102] Figure 3 This is a schematic diagram of an improved IEEE-33 node model in Example 1 of the present invention.

[0103] Figure 4 This is a typical scenario of the new energy output and load demand generated in Example 1 of the present invention.

[0104] Figure 5 It is a system diagram of the present invention. DETAILED DESCRIPTION

[0105] The present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0106] The new energy mentioned in the present invention refers to the renewable resource power generation mode except hydropower generation.

[0107] Embodiment 1:

[0108] See also Figures 1 to 4 ,This embodiment uses the modified IEEE standard 39-bus system as the research power system. Figure 3 As shown, the system has 4 thermal power units with a total installed capacity of 1806MW, 4 hydropower stations with a total installed capacity of 15 hydropower units with a total installed capacity of 3145MW, a total installed capacity of 2050MW for wind power, and a total installed capacity of 1315MW for photovoltaic power. This embodiment specifically adopts the following technical solutions to realize the cascade hydropower integration transformation and grid planning coordination method to improve system flexibility:

[0109] S1. Generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand;

[0110] S11. Establishing an improved generative adversarial network model with gradient penalty for the characteristics of renewable energy output and load demand respectively; the dimension of the improved generative adversarial network model with gradient penalty is consistent with the data dimension of renewable energy output and load demand, and can learn the data distribution characteristics of renewable energy output and load demand;

[0111] S12, randomly selecting 80% of the new energy output data and load demand data as training data, and the rest as test data, and inputting the training data into the constructed generative adversarial network model for training;

[0112] S13, after the training is completed, extract the generator in the trained network, take the noise data that obeys the normal distribution as input, and generate the scene sets of new energy output and load demand respectively; the noise data that obeys the normal distribution is randomly generated noise data that obeys the 0-1 normal distribution;

[0113] S14. Use the K-means clustering method to cluster the generated new energy output and load demand scenarios respectively, obtain several typical scenarios of new energy output and load demand, and combine several typical scenarios of new energy output with several typical scenarios of load demand to obtain a typical scenario set Γ. That is, a typical scenario of new energy output is combined with a typical scenario of load demand to obtain a typical scenario in the typical scenario set Γ. The typical scenario set Γ is a set of typical scenarios including all possible combinations. The obtained typical scenarios are as follows: Figure 4 shown.

[0114] S2. Establish a two-layer optimization model based on typical scenarios in MATLAB software. According to the obtained typical scenario set and the flexibility evaluation index of the power system, establish a two-layer optimization configuration model to improve the flexibility of the system, including the upper-layer cascade hydropower integration transformation and grid planning model and the lower-layer operation model;

[0115] In S2, the flexibility evaluation index of the power system includes: a system node flexibility evaluation index and a system network flexibility evaluation index;

[0116] The calculation formula of the system node flexibility evaluation index is as follows:

[0117]

[0118] In the above formula, F node,s is the node flexibility index of the system under the typical scenario s, T is the flexibility evaluation time period, and F node,s,t is the node flexibility index at time t in a typical scenario s, are the upper and lower adjustment point flexibility indicators of the system at time t in a typical scenario s, They are the upward and downward flexibility requirements of the system at time t in a typical scenario s, They are the upward and downward flexibility supply of the system at time t under the typical scenario s;

[0119] Said It is calculated using the following formula:

[0120]

[0121] In the above formula, are the maximum and minimum controllable power requirements of the system at time t+1 under typical scenario s, are the maximum and minimum controllable power requirements of the system at time t under typical scenario s, They are the upward and downward flexibility supply of thermal power units at time t under typical scenario s, They are the upward and downward flexibility supply of hydropower units at time t under typical scenario s, They are respectively the upward and downward flexibility supply of the pumped storage unit at time t under the typical scenario s; It is calculated using the following formula:

[0122]

[0123]

[0124] In the above formula, N th is the number of thermal power units in the system, γ th,g,s,t , P th,g,s,tare the start / stop status and output power of thermal power unit g at time t under typical scenario s, P th,g,max , P th,g,min are the upper and lower limits of the output of thermal power unit g, are the upward and downward climbing rates of thermal power unit g, Δt is the scheduling time interval, I is the number of hydropower stations, N i is the number of hydropower units in hydropower station i, u i,n,s,t , P i,n,s,t is the start / stop status and output of the nth unit of hydropower station i in period t under typical scenario s, P i,n are the upper and lower limits of the output of the nth unit of hydropower station i, are the upward and downward climbing rates of the nth unit of hydropower station i, N pum,i is the number of pumped storage units in hydropower station i, P vp,i,m,s,t、 P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,max,i,m、 P vg,max,i,m are the maximum pumping power and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. are the upward and downward climbing rates of the mth pumped storage unit of hydropower station i respectively; the calculation formula of the system network transmission flexibility evaluation index is as follows:

[0125]

[0126] F s,j,u =A s,j,u +λB s,j,u ; F s,j,d =A s,j,d +λB s,j,d ;

[0127] In the above formula, F net,s is the network transmission flexibility index in the system time period T under the typical scenario s, N is the number of lines, and F net,s,j is the network transmission flexibility index of line j in time period T under typical scenario s, s,j,u 、F s,j,d are the comprehensive indicators of insufficient flexibility of upward and downward adjustment of line j, A s,j,u , A s,j,d are the average insufficient flexibility load for upward and downward adjustment of line j, λ is the weight factor, B s,j,u , B s,j,d are the discrete degrees of insufficient flexibility carrying capacity for upward and downward adjustment of line j respectively; s,j,u , A s,j,d , B s,j,u , Bs,j,d It is calculated using the following formula:

[0128]

[0129] In the above formula, G s,j,u,t , G s,j,d,t are the transmission margins of up and down line flexibility of line j at time t in typical scenario s, T s,j,u 、T s,j,d are the sum of the periods of insufficient upward and downward flexibility of line j in typical scenario s; s,j,u,t , G s,j,d,t It is calculated using the following formula:

[0130]

[0131] In the above formula, P max,j is the maximum permissible transmission capacity of line j, P s,j,t is the transmission power value of line j at time t in typical scenario s, are the allocation of upward and downward flexibility demands of the system at time t on line j under typical scenario s, are respectively the allocation of upward and downward flexibility supply of the system at time t on line j under typical scenario s; The following calculation formula is used:

[0132]

[0133] In the above formula, M is the number of nodes in the system, is the power transmission distribution factor of node k’s injected power to line j in typical scenario s, are the upward and downward flexibility requirements of node k at time t in a typical scenario s, They are respectively the upward and downward flexibility supply of node k at time t in the typical scenario s.

[0134] In S2, the objective function of the upper cascade hydropower integration transformation and grid planning model is:

[0135] f 1 =min{C total ,F′ node ,F′ net};

[0136]

[0137] In the above formula, C total is the total annual cost of the power system, F n ' ode 、Fn ' et are the node and network transmission flexibility evaluation indicators of the system, C con is the equivalent annual construction and maintenance cost, is the probability of a typical scene s appearing, C oper,s is the annual operating cost under the typical scenario s, F node,s 、F net,s are the node and network transmission flexibility evaluation indicators under typical scenario s, respectively, and Γ is the set of typical scenarios;

[0138] The objective function of the lower-level running model is:

[0139]

[0140] In the above formula, C G,s , are the annual power generation cost, annual penalty cost for abandoning new energy, and annual penalty cost for load shedding of the system under the typical scenario s, respectively. g 、b g 、c g are the power generation cost coefficients of thermal power unit g, P th,g,s,t is the output power of thermal power unit g under typical scenario s at time t, c re 、c load They are the penalty cost coefficient for abandoning new energy and the penalty cost coefficient for load shedding, P re,k,s,t are the maximum output power and actual absorption power of the new energy of node k in the typical scenario s at time t, P load,k,s,t are the power supply required and actual power supply of node k in typical scenario s at time t, G th , G re , Π are controllable power supply units, new energy, and system node collection respectively.

[0141] The constraints of the upper-level planning model include pumped storage units and line planning and construction constraints, including:

[0142]

[0143] In the above formula, x i The number of pumped storage units added at the hydropower station i, are the upper and lower limits of the number of additional pumped storage units to be built at hydropower station i, l j is the number of newly built lines j, are the upper and lower limits of the number of newly built lines j, is the equivalent annual construction and maintenance cost cap, Π 1 A collection of hydropower stations to be built with pumped storage units. 2is a collection of lines to be built;

[0144] The constraints of the lower-level operation model include: power flow balance constraints, line capacity constraints, thermal power output constraints, hydropower output constraints, pumped storage operation constraints, and node voltage phase angle constraints. The formula is as follows:

[0145] a. Power flow balance constraints:

[0146] In the above formula, P th,s , P hy,s , P re,s , P load,s They are the output vector of thermal power units, the output vector of hydropower units, the output vector of new energy units, and the node load vector under the typical scenario s. are respectively the pumped storage power generation and pumped hydropower vectors, B is the node admittance matrix, θ s is the node voltage phase angle vector under typical scenario s;

[0147] b. Line capacity constraints:

[0148] In the above formula, is the number of line j before expansion, P j ' ,max is the transmission capacity of a single line j;

[0149] c. Thermal power output constraints

[0150] d. Hydropower output constraints include hydropower station constraints and hydropower unit constraints;

[0151] d1. Hydropower station constraints include hydraulic connection constraints, water level constraints, outflow constraints, hydropower station output constraints, water level-reservoir capacity relationship constraints, and tailwater level-discharge relationship constraints:

[0152] Hydraulic connection constraint: V i,s,t =V i,s,t-1 +3600(I i,s,t -Q i,s,t )Δt;

[0153]

[0154]

[0155] Water level constraints:

[0156] Outbound traffic constraints:

[0157] Hydropower station output constraints:

[0158] Water level-reservoir capacity relationship constraints:

[0159] Tailwater level-discharge relationship constraints:

[0160] In the above formula, V i,s,t is the storage capacity of hydropower station i in period t under typical scenario s, I i,s,t is the inflow of hydropower station i in period t under typical scenario s, Q i,s,t is the outflow of hydropower station i in period t under typical scenario s, τ is the water lag time between hydropower station i and its upstream hydropower station i-1, Q i-1,s,t-τ is the outflow of hydropower station i-1 in period t-τ after considering water lag under typical scenario s; R i,s,t is the interval flow between hydropower station i-1 and hydropower station i in period t under typical scenario s, are the pumping and power generation flows of the pumped storage unit i in the typical scenario s, are respectively the power generation and abandoned water flow of hydropower station i in period t under typical scenario s, is the water level in front of the dam of hydropower station i in the reservoir at time period t under typical scenario s, Z i up are the upper and lower limits of the water level in front of the dam of the hydropower station i in the reservoir where it is located, is the initial water level during the scheduling period under the typical scenario s, Q i are the upper and lower limits of the outflow flow of hydropower station i, is the output of hydropower station i in period t under typical scenario s, P i hydro are the upper and lower limits of the output of hydropower station i, respectively, and f i zv (·) is the nonlinear relationship curve function between water level and storage capacity of the reservoir where the hydropower station i is located, f i zq (·) is the nonlinear relationship curve function between the tailwater level and discharge flow of hydropower station i, is the tailwater level of hydropower station i in period t under typical scenario s;

[0161] d2. Hydropower unit constraints include: unit output constraints, unit power flow constraints, unit start-up and shutdown duration constraints, unit output ramp constraints, unit power head constraints, and unit power characteristic constraints:

[0162] Unit output constraints:

[0163] Unit power generation flow constraints:

[0164] Unit start-up and shutdown duration constraints:

[0165] Unit output ramp constraint: -ΔP i,n ≤P i,n,s,t+1 -P i,n,s,t ≤ΔP i,n ;

[0166] Unit generating head constraints:

[0167] Unit power characteristic constraints:

[0168] In the above formula, u i,n,s,t is the start-up and shutdown state variable of the nth unit of hydropower station i in period t under typical scenario s, u i,n,s,t ∈{0,1};P i,n,s,t is the output of the nth unit of hydropower station i in period t under typical scenario s; P i ,n are the upper and lower limits of the output of the nth unit of the hydropower station i, 1 represents the start state, and 0 represents the shutdown state; N i is the total number of units included in hydropower station i; is the power generation flow of the nth unit of hydropower station i in period t under typical scenario s, are the upper and lower limits of the power generation flow of the nth unit of hydropower station i, respectively; are the startup and shutdown operation variables of the nth unit of hydropower station i in period t under typical scenario s; are the minimum startup and shutdown durations of the nth unit of hydropower station i, respectively; is the maximum number of startup times of the nth unit of hydropower station i during the dispatch period; ΔP i,n is the climbing capacity of the nth unit of the hydropower station i; H i,n,s,t is the generating head of the nth unit of hydropower station i in period t under typical scenario s; is the nonlinear relationship function of output-head-flow of the nth unit of hydropower station i;

[0169] e. The pumped storage operation constraints:

[0170]

[0171] In the above formula, x vp,i,m,s,t 、x vg,i,m,s,tare the pumping and power generation states of the mth pumped storage unit of hydropower station i in the typical scenario s in time period t. When the value is 1, it means it is in this state, and when the value is 0, it means it is not in this state. vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,min,i,m , P vp,max,i,m , P vg,min,i,m , P vg,max,i,m are the minimum pumping power, maximum pumping power, minimum generating power, and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. vp,i,m,s,t , Q vg,i,m,s,t are the pumping and power generation flows of the mth pumped-storage unit of hydropower station i in period t under typical scenario s, η p , η g are the pumping and power generation efficiencies of a single pumped storage unit, ρ 0 , g are the average density of water and the acceleration due to gravity, h i,s is the average water head of hydropower station i under typical scenario s, N pum,i is the number of pumped storage units in hydropower station i;

[0172] f. Node voltage phase angle constraint:

[0173] In the above formula, θ k,s,t is the voltage phase angle of node k in period t under typical scenario s, They are the upper and lower limits of the voltage phase angle at node k respectively.

[0174] S3. Use the multi-objective whale algorithm and Gurobi solver to solve the above two-layer optimization configuration model to obtain the system cascade hydropower integration transformation and grid planning scheme;

[0175] In S3, the specific operation method for solving the two-layer optimization model includes:

[0176] S31, nonlinear equation constraints of the linearized inner model, including water level-storage capacity relationship constraints, tailwater level-discharge relationship constraints, and unit dynamic characteristics constraints;

[0177] The specific operation method of the nonlinear equation of the linearized inner model: water level-reservoir capacity relationship constraint includes:

[0178] First, the water level in front of the reservoir where the hydropower station i is located is discretized into N 1 Intervals:

[0179]

[0180] In the above formula, is the nth interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity;

[0181] Then, the water level in front of the dam of the reservoir where the hydropower station i is located in the typical scenario s in time period t can be expressed as:

[0182]

[0183] In the above formula, is an indicator variable. When the water level in front of the dam of the reservoir where the hydropower station i is located in the typical scenario s is in the nth interval in time period t, otherwise, is the water level in front of the dam of hydropower station i in the nth interval under the typical scenario s;

[0184] The storage capacity of the reservoir where the hydropower station i is located in the typical scenario s in the period t, completes the linearization of the nonlinear relationship curve function between water level and storage capacity;

[0185]

[0186] In the above formula, V i n-1 is the n-1th interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity;

[0187] The specific operation method of the nonlinear equation of the linearized inner layer model: the specific operation method of the tailwater level-discharge relationship constraint includes:

[0188] First, the outflow of hydropower station i is discretized into N 2 Intervals:

[0189]

[0190] In the above formula, is the nth interpolation point of the outflow of hydropower station i and its corresponding tailwater level;

[0191] Then, the outflow of hydropower station i under typical scenario s can be expressed as:

[0192]

[0193] In the above formula, is an indicator variable. When the outflow of hydropower station i in period t under typical scenario s is in the nth interval, otherwise, is the outflow of hydropower station i in the nth interval under typical scenario s;

[0194] The tailwater level of the reservoir where the hydropower station i is located in the typical scenario s during the period t, and the linearization of the nonlinear relationship curve function between tailwater level and discharge volume is completed;

[0195]

[0196] In the above formula, is the n-1th interpolation point of the outflow of hydropower station i and its corresponding tailwater level;

[0197] The specific operation method of the nonlinear equation unit dynamic characteristic constraint of the linearized inner model includes:

[0198] The unit dynamic characteristic constraints are transformed into the following form using McCormick convex envelope relaxation method to complete the linearization of the nonlinear unit dynamic characteristic constraints:

[0199]

[0200] In the above formula, η i,n is the power generation efficiency of the nth unit of hydropower station i, They are the upper and lower limits of the generating head of the nth unit of hydropower station i.

[0201] S32, initialize the parameters of the multi-objective whale algorithm, set the algorithm population size to 30, the maximum number of iterations to 40, and the random pumped storage energy expansion and line configuration initial plan, where the upper and lower limits of the power generation capacity of a single pumped storage unit are both 100MW;

[0202] S33, bringing the initial plan of pumped storage expansion and line configuration into the linearized lower model, calling the Gurobi mathematical solver to solve the lower model for the generated typical scenario, and passing the obtained system flow data to the upper model;

[0203] S34. Calculate the objective function value of the upper model for the generated typical scenario and the flow data transmitted by the lower model, solve the upper model using the multi-objective whale algorithm, and obtain the pumped storage expansion and line configuration plan;

[0204] S35. Determine whether the maximum number of iterations has been reached. If so, output the pumped storage expansion and line configuration plan. Otherwise, update the pumped storage expansion and line configuration plan and repeat steps S33-S35.

[0205] The results of pumped storage expansion and line configuration using the multi-objective whale algorithm are shown in Table 1.

[0206] Table 1 Configuration scheme

[0207]

[0208] S4. Evaluate the effect of cascade hydropower integration transformation and grid planning synergy on improving system flexibility.

[0209] The node flexibility and network transmission flexibility of the system before and after pumped storage and line configuration are compared to evaluate the improvement effect of cascade hydropower integration transformation and grid planning coordination method on system flexibility. The node flexibility and network transmission flexibility evaluation indicators of the system before and after pumped storage and line configuration are calculated respectively, and the results are shown in Table 2.

[0210] Table 2 System evaluation results

[0211]

[0212] It can be seen that in this example, a coordinated method of cascade hydropower integration transformation and grid planning to improve system flexibility can effectively improve system flexibility, reduce wind and solar power abandonment, and promote the consumption of new energy.

[0213] Embodiment 2:

[0214] See also Figure 5 , a cascade hydropower integration transformation and grid planning coordination system to improve system flexibility, including: a typical scenario set generation module, a two-layer optimization configuration model construction module, and a model solution module;

[0215] Typical scenario set generation module: used to generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand, and obtain typical scenario sets;

[0216] Two-layer optimization configuration model building module: used to establish a two-layer optimization configuration model to improve system flexibility based on the obtained typical scenario set and the flexibility evaluation index of the power system, including the upper-layer cascade hydropower integration transformation and grid planning model and the lower-layer operation model;

[0217] Model solving module: It is used to solve the above two-layer optimization configuration model using the multi-objective whale algorithm and Gurobi solver to obtain the system cascade hydropower integration transformation and grid planning scheme.

[0218] Embodiment 3:

[0219] A cascade hydropower integration transformation and grid planning coordination device for improving system flexibility, the device comprising a processor and a memory;

[0220] The memory is used to store computer program code and transmit the computer program code to the processor;

[0221] The processor is used to execute the coordinated method of cascade hydropower integration transformation and grid planning for improving system flexibility described in Example 1 according to the instructions in the computer program code.

[0222] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method for coordinating cascade hydropower integration transformation and grid planning for improving system flexibility as described in Example 1.

Claims

1. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility, characterized in that: include: S1. Generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand, and obtain a typical scenario set; S2. Based on the obtained typical scenario set and the flexibility evaluation index of the power system, a two-layer optimization configuration model for improving system flexibility is established, including an upper-layer cascade hydropower integration transformation and grid planning model and a lower-layer operation model; S3. The multi-objective whale algorithm and Gurobi solver are used to solve the above two-layer optimization configuration model to obtain the system cascade hydropower integration transformation and grid planning scheme.

2. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 1, characterized in that: The S1 includes: S11. Establishing an improved generative adversarial network model with gradient penalty for the characteristics of renewable energy output and load demand respectively; the dimension of the improved generative adversarial network model with gradient penalty is consistent with the data dimension of renewable energy output and load demand, and can learn the data distribution characteristics of renewable energy output and load demand; S12, randomly selecting 80% of the new energy output data and load demand data as training data, and the rest as test data, and inputting the training data into the constructed generative adversarial network model for training; S13, after the training is completed, extract the generator in the trained network, use the noise data that obeys the normal distribution as input, and generate the scenario sets of new energy output and load demand respectively; S14. Use the K-means clustering method to cluster the generated renewable energy output and load demand scenarios respectively, obtain several typical renewable energy output and load demand scenarios, and combine the two to obtain a typical scenario set Γ.

3. The method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 1, characterized in that: In S2, the flexibility evaluation index of the power system includes: a system node flexibility evaluation index and a system network flexibility evaluation index; The calculation formula of the system node flexibility evaluation index is as follows: In the above formula, F node,s is the node flexibility index of the system under typical scenario s, T is the flexibility evaluation time period, and F node,s,t is the node flexibility index at time t in a typical scenario s, are the upper and lower adjustment point flexibility indicators of the system at time t in a typical scenario s, They are the upward and downward flexibility requirements of the system at time t in a typical scenario s, They are the upward and downward flexibility supply of the system at time t under the typical scenario s; Said It is calculated using the following formula: In the above formula, are the maximum and minimum controllable power requirements of the system at time t+1 under typical scenario s, are the maximum and minimum controllable power requirements of the system at time t under typical scenario s, They are the upward and downward flexibility supply of thermal power units at time t under typical scenario s, They are the upward and downward flexibility supply of hydropower units at time t under typical scenario s, They are respectively the upward and downward flexibility supply of the pumped storage unit at time t under the typical scenario s; It is calculated using the following formula: In the above formula, N th is the number of thermal power units in the system, γ th,g,s,t、 P th,g,s,t are the start / stop status and output power of thermal power unit g at time t under typical scenario s, P th,g,max , P th,g,min are the upper and lower limits of the output of thermal power unit g, are the upward and downward climbing rates of thermal power unit g, Δt is the scheduling time interval, I is the number of hydropower stations, N i is the number of hydropower units in hydropower station i, u i,n,s,t , P i,n,s,t is the start / stop status and output of the nth unit of hydropower station i in period t under typical scenario s, P i ,n are the upper and lower limits of the output of the nth unit of hydropower station i, are the upward and downward climbing rates of the nth unit of hydropower station i, N pum,i is the number of pumped storage units in hydropower station i, P vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,max,i,m、 P vg,max,i,m are the maximum pumping power and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. are the upward and downward climbing rates of the mth pumped storage unit of hydropower station i respectively; the calculation formula of the system network transmission flexibility evaluation index is as follows: F s,j,u =A s,j,u +λB s,j,u ;F s,j,d =A s,j,d +λB s,j,d ; In the above formula, F net,s is the network transmission flexibility index in the system time period T under the typical scenario s, N is the number of lines, and F net,s,j is the network transmission flexibility index of line j in time period T under typical scenario s, s,j,u 、F s,j,d are the comprehensive indicators of insufficient flexibility of upward and downward adjustment of line j, A s,j,u , A s,j,d are the average insufficient flexibility load for upward and downward adjustment of line j, λ is the weight factor, B s,j,u , B s,j,d are the discrete degrees of insufficient flexibility carrying capacity for upward and downward adjustment of line j respectively; s,j,u , A s,j,d , B s,j,u , B s,j,d It is calculated using the following formula: In the above formula, G s,j,u,t , G s,j,d,t are the transmission margins of up and down line flexibility of line j at time t in typical scenario s, T s,j,u 、T s,j,d are the sum of the periods of insufficient upward and downward flexibility of line j in typical scenario s; s,j,u,t , G s,j,d,t It is calculated using the following formula: In the above formula, P max,j is the maximum permissible transmission capacity of line j, P s,j,t is the transmission power value of line j at time t in typical scenario s, are the allocation of upward and downward flexibility demands of the system at time t on line j under typical scenario s, are respectively the allocation of upward and downward flexibility supply of the system at time t on line j under typical scenario s; The following calculation formula is used: In the above formula, M is the number of nodes in the system, is the power transmission distribution factor of node k’s injected power to line j in typical scenario s, are the upward and downward flexibility requirements of node k at time t in a typical scenario s, They are respectively the upward and downward flexibility supply of node k at time t in typical scenario s.

4. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 3, characterized in that: In S2, the objective function of the upper cascade hydropower integration transformation and grid planning model is: f1=min{C total ,F n ′ ode ,F n ′ et }; In the above formula, C total is the total annual cost of the power system, F n ' ode 、F n ' et are the node and network transmission flexibility evaluation indicators of the system, C con is the equivalent annual construction and maintenance cost, is the probability of a typical scene s appearing, C oper,s is the annual operating cost under the typical scenario s, F node,s 、F net,s are the node and network transmission flexibility evaluation indicators under typical scenario s, respectively, and Γ is the set of typical scenarios; The objective function of the lower-level running model is: In the above formula, C G,s , are the annual power generation cost, annual penalty cost for abandoning new energy, and annual penalty cost for load shedding of the system under the typical scenario s, respectively. g , b g 、c g are the power generation cost coefficients of thermal power unit g, P th,g,s,t is the output power of thermal power unit g under typical scenario s at time t, c re 、c load They are the penalty cost coefficient for abandoning new energy and the penalty cost coefficient for load shedding, P re,k,s,t are the maximum output power and actual absorption power of the new energy of node k in the typical scenario s at time t, P load,k,s,t are the power supply required and actual power supply of node k in typical scenario s at time t, G th , G re , Π are controllable power supply units, new energy, and system node collection respectively.

5. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 4, characterized in that: The constraints of the upper-level planning model include pumped storage units and line planning and construction constraints, including: In the above formula, x i The number of pumped storage units added at the hydropower station i, are the upper and lower limits of the number of additional pumped storage units to be built at hydropower station i, l j is the number of newly built lines j, are the upper and lower limits of the number of newly built lines j, is the upper limit of equivalent annual construction and maintenance cost, Π1 is the set of hydropower stations to be built with pumped storage units, and Π2 is the set of lines to be built; The constraints of the lower-level operation model include: power flow balance constraints, line capacity constraints, thermal power output constraints, hydropower output constraints, pumped storage operation constraints, and node voltage phase angle constraints. The formula is as follows: a. Power flow balance constraints: In the above formula, P th,s , P hy,s , P re,s , P load,s They are the output vector of thermal power units, the output vector of hydropower units, the output vector of new energy units, and the node load vector under the typical scenario s. are respectively the pumped storage power generation and pumped hydropower vectors, B is the node admittance matrix, θ s is the node voltage phase angle vector under typical scenario s; b. Line capacity constraints: In the above formula, is the number of line j before expansion, P j ' ,max is the transmission capacity of a single line j; c. Thermal power output constraints d. Hydropower output constraints include hydropower station constraints and hydropower unit constraints; d1. Hydropower station constraints include hydraulic connection constraints, water level constraints, outflow constraints, hydropower station output constraints, water level-reservoir capacity relationship constraints, and tailwater level-discharge relationship constraints: Hydraulic connection constraint: V i,s,t =V i,s,t-1 +3600(I i,s,t -Q i,s,t )Δt; Water level constraints: Outbound traffic constraints: Hydropower station output constraints: Water level-reservoir capacity relationship constraints: Tailwater level-discharge relationship constraints: In the above formula, V i,s,t is the storage capacity of hydropower station i in period t under typical scenario s, I i,s,t is the inflow of hydropower station i in period t under typical scenario s, Q i,s,t is the outflow of hydropower station i in period t under typical scenario s, τ is the water lag time between hydropower station i and its upstream hydropower station i-1, Q i-1,s,t-τ is the outflow of hydropower station i-1 in period t-τ after considering water lag under typical scenario s; R i,s,t is the interval flow between hydropower station i-1 and hydropower station i in period t under typical scenario s, are the pumping and power generation flows of the pumped storage unit i in the typical scenario s, are respectively the power generation and abandoned water flow of hydropower station i in period t under typical scenario s, is the water level in front of the dam of hydropower station i in the reservoir at time period t under typical scenario s, are the upper and lower limits of the water level in front of the dam of the hydropower station i in the reservoir where it is located, is the initial water level during the scheduling period under the typical scenario s, Q i are the upper and lower limits of the outflow flow of hydropower station i, is the output of hydropower station i in period t under typical scenario s, P i hydro are the upper and lower limits of the output of hydropower station i, respectively, and f i zv (·) is the nonlinear relationship curve function between water level and storage capacity of the reservoir where the hydropower station i is located, f i zq (·) is the nonlinear relationship curve function between the tailwater level and discharge flow of hydropower station i, is the tailwater level of hydropower station i in period t under typical scenario s; d2. Hydropower unit constraints include: unit output constraints, unit power flow constraints, unit start-up and shutdown duration constraints, unit output ramp constraints, unit power head constraints, and unit power characteristic constraints: Unit output constraints: Unit power generation flow constraints: Unit start-up and shutdown duration constraints: Unit output ramp constraint: -ΔP i,n ≤P i,n,s,t+1 -P i,n,s,t ≤ΔP i,n ; Unit generating head constraints: Unit power characteristic constraints: In the above formula, u i,n,s,t is the start-up and shutdown state variable of the nth unit of hydropower station i in period t under typical scenario s, u i,n,s,t ∈{0,1};P i,n,s,t is the output of the nth unit of hydropower station i in period t under typical scenario s; P i ,n are the upper and lower limits of the output of the nth unit of the hydropower station i, 1 represents the start state, and 0 represents the shutdown state; N i is the total number of units included in hydropower station i; is the power generation flow of the nth unit of hydropower station i in period t under typical scenario s, are the upper and lower limits of the power generation flow of the nth unit of hydropower station i, respectively; are the startup and shutdown operation variables of the nth unit of hydropower station i in period t under typical scenario s; are the minimum startup and shutdown durations of the nth unit of hydropower station i, respectively; is the maximum number of startup times of the nth unit of hydropower station i during the dispatch period; ΔP i,n is the climbing capacity of the nth unit of the hydropower station i; H i,n,s,t is the generating head of the nth unit of hydropower station i in period t under typical scenario s; is the nonlinear relationship function of output-head-flow of the nth unit of hydropower station i; e. The pumped storage operation constraints: x vp,i,m,s,t +x vg,i,m,s,t ≤1; P vp,min x vp,i,m,s,t≤ P vp,i,m,s,t ≤P vp,max x vp,i,m,s,t； P vg,min x vg,i,m,s,t ≤P vg,i,m,s,t ≤P vg,max x vg,i,m,s,t ; In the above formula, x vp,i,m,s,t 、x vg,i,m,s,t are the pumping and power generation states of the mth pumped storage unit of hydropower station i in the typical scenario s in time period t. When the value is 1, it means it is in this state, and when the value is 0, it means it is not in this state. vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,min,i,m , P vp,max,i,m , P vg,min,i,m , P vg,max,i,m are the minimum pumping power, maximum pumping power, minimum generating power, and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. vp,i,m,s,t , Q vg,i,m,s,t are the pumping and power generation flows of the mth pumped-storage unit of hydropower station i in period t under typical scenario s, η p , η g are the pumping and power generation efficiencies of a single pumped storage unit, ρ0 and g are the average density of water and gravitational acceleration, respectively, and h i,s is the average water head of hydropower station i under typical scenario s, N pum,i is the number of pumped storage units in hydropower station i; f. Node voltage phase angle constraint: In the above formula, θ k,s,t is the voltage phase angle of node k in period t under typical scenario s, They are the upper and lower limits of the voltage phase angle at node k respectively.

6. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 5, characterized in that: In S3, the specific operation method for solving the two-layer optimization model includes: S31, nonlinear equation constraints of the linearized inner model, including water level-storage capacity relationship constraints, tailwater level-discharge relationship constraints, and unit dynamic characteristics constraints; S32, initializing the parameters of the multi-objective whale algorithm, including the population number of the algorithm, the maximum number of iterations, and the random pumped storage expansion and line configuration initial plan; S33, bringing the initial plan of pumped storage expansion and line configuration into the linearized lower model, calling the Gurobi mathematical solver to solve the lower model for the generated typical scenario, and passing the obtained system flow data to the upper model; S34. Calculate the objective function value of the upper model for the generated typical scenario and the flow data transmitted by the lower model, solve the upper model using the multi-objective whale algorithm, and obtain the pumped storage expansion and line configuration plan; S35. Determine whether the maximum number of iterations has been reached. If so, output the pumped storage expansion and line configuration plan. Otherwise, update the pumped storage expansion and line configuration plan and repeat steps S33-S35.

7. A method for coordinating cascade hydropower integration transformation and grid planning to improve system flexibility according to claim 6, characterized in that: The nonlinear equation water level-storage capacity relationship constraint of the linearized inner layer model is obtained: In the above formula, is the nth interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity; is the n-1th interpolation point of the water level in front of the dam of the reservoir where the hydropower station i is located and its corresponding reservoir capacity; is an indicator variable. When the water level in front of the dam of the reservoir where the hydropower station i is located in the typical scenario s is in the nth interval in time period t, otherwise, is the water level in front of the dam of hydropower station i in the nth interval under the typical scenario s; The nonlinear equation of the tailwater level-discharge relationship constraint of the linearized inner layer model is obtained: In the above formula, is the nth interpolation point of the outflow of hydropower station i and its corresponding tailwater level; is the n-1th interpolation point of the outflow of hydropower station i and its corresponding tailwater level; is an indicator variable. When the outflow of hydropower station i in period t under typical scenario s is in the nth interval, otherwise, is the outflow of hydropower station i in the nth interval under typical scenario s; The specific operation method of the nonlinear equation unit dynamic characteristic constraint of the linearized inner model includes: The unit dynamic characteristic constraints are transformed into the following form using McCormick convex envelope relaxation method to complete the linearization of the nonlinear unit dynamic characteristic constraints: In the above formula, η i,n is the power generation efficiency of the nth unit of hydropower station i, They are the upper and lower limits of the generating head of the nth unit of hydropower station i.

8. A cascade hydropower integration transformation and grid planning coordination system to improve system flexibility, characterized by: include: Typical scenario set generation module, two-layer optimization configuration model construction module, model solving module; Typical scenario set generation module: used to generate typical scenarios of new energy output and load demand based on historical data of new energy output and load demand, and obtain typical scenario sets; Two-layer optimization configuration model building module: used to establish a two-layer optimization configuration model to improve system flexibility based on the obtained typical scenario set and the flexibility evaluation index of the power system, including the upper-layer cascade hydropower integration transformation and grid planning model and the lower-layer operation model; Model solving module: It is used to solve the above two-layer optimization configuration model using the multi-objective whale algorithm and Gurobi solver to obtain the system cascade hydropower integration transformation and grid planning scheme.

9. The cascade hydropower integration transformation and grid planning coordination system for improving system flexibility according to claim 8, characterized in that: The objective function of the upper cascade hydropower integration transformation and grid planning model is: f1=min{C total ,F′ node ,F′ net }; In the above formula, C total is the total annual cost of the power system, F′ node , F′ net are the node and network transmission flexibility evaluation indicators of the system, C con is the equivalent annual construction and maintenance cost, is the probability of a typical scene s appearing, C oper,s is the annual operating cost under the typical scenario s, F node,s 、F net,s are the node and network transmission flexibility evaluation indicators under typical scenario s, respectively, and Γ is the set of typical scenarios; The objective function of the lower-level running model is: In the above formula, C G,s , are the annual power generation cost, annual penalty cost for abandoning new energy, and annual penalty cost for load shedding of the system under the typical scenario s, respectively. g , b g 、c g are the power generation cost coefficients of thermal power unit g, P th,g,s,t is the output power of thermal power unit g under typical scenario s at time t, c re 、c load They are the penalty cost coefficient for abandoning new energy and the penalty cost coefficient for load shedding, P re,k,s,t are the maximum output power and actual absorption power of the new energy of node k in the typical scenario s at time t, P load,k,s,t are the power supply required and actual power supply of node k in typical scenario s at time t, G th , G re , Π are controllable power supply units, new energy, and system node collection respectively.

10. A cascade hydropower integration transformation and grid planning coordination system for improving system flexibility according to claim 9, characterized in that: The flexibility evaluation indicators of the power system include: system node flexibility evaluation indicators, system network flexibility evaluation indicators; The calculation formula of the system node flexibility evaluation index is as follows: In the above formula, F node,s is the node flexibility index of the system under typical scenario s, T is the flexibility evaluation time period, and F node,s,t is the node flexibility index at time t in a typical scenario s, are the upper and lower adjustment point flexibility indicators of the system at time t in a typical scenario s, They are the upward and downward flexibility requirements of the system at time t in a typical scenario s, They are the upward and downward flexibility supply of the system at time t under the typical scenario s; Said It is calculated using the following formula: In the above formula, are the maximum and minimum controllable power requirements of the system at time t+1 under typical scenario s, are the maximum and minimum controllable power requirements of the system at time t under typical scenario s, They are the upward and downward flexibility supply of thermal power units at time t under typical scenario s, They are the upward and downward flexibility supply of hydropower units at time t under typical scenario s, They are respectively the upward and downward flexibility supply of the pumped storage unit at time t under the typical scenario s; It is calculated using the following formula: In the above formula, N th is the number of thermal power units in the system, γ th,g,s,t , P th,g,s,t are the start / stop status and output power of thermal power unit g at time t under typical scenario s, P th,g,max , P th,g,min are the upper and lower limits of the output of thermal power unit g, are the upward and downward climbing rates of thermal power unit g, Δt is the scheduling time interval, I is the number of hydropower stations, N i is the number of hydropower units in hydropower station i, u i,n,s,t , P i,n,s,t is the start / stop status and output of the nth unit of hydropower station i in period t under typical scenario s, P i ,n are the upper and lower limits of the output of the nth unit of hydropower station i, are the upward and downward climbing rates of the nth unit of hydropower station i, N pum,i is the number of pumped storage units in hydropower station i, P vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,max,i,m、 P vg,max,i,m are the maximum pumping power and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. are the upward and downward climbing rates of the mth pumped storage unit of hydropower station i respectively; the calculation formula of the system network transmission flexibility evaluation index is as follows: F s,j,u =A s,j,u +λB s,j,u ;F s,j,d =A s,j,d +λB s,j,d ; In the above formula, F net,s is the network transmission flexibility index in the system time period T under the typical scenario s, N is the number of lines, and F net,s,j is the network transmission flexibility index of line j in time period T under typical scenario s, s,j,u 、F s,j,d are the comprehensive indicators of insufficient flexibility of upward and downward adjustment of line j, A s,j,u , A s,j,d are the average insufficient flexibility load for upward and downward adjustment of line j, λ is the weight factor, B s,j,u , B s,j,d are the discrete degrees of insufficient flexibility carrying capacity for upward and downward adjustment of line j respectively; s,j,u , A s,j,d , B s,j,u , B s,j,d It is calculated using the following formula: In the above formula, G s,j,u,t , G s,j,d,t are the transmission margins of up and down line flexibility of line j at time t in typical scenario s, T s,j,u 、T s,j,d are the sum of the periods of insufficient upward and downward flexibility of line j in typical scenario s; s,j,u,t , G s,j,d,t It is calculated using the following formula: In the above formula, P max,j is the maximum permissible transmission capacity of line j, P s,j,t is the transmission power value of line j at time t in typical scenario s, are the allocation of upward and downward flexibility demands of the system at time t on line j under typical scenario s, are respectively the allocation of upward and downward flexibility supply of the system at time t on line j under typical scenario s; The following calculation formula is used: In the above formula, M is the number of nodes in the system, is the power transmission distribution factor of node k’s injected power to line j in typical scenario s, are the upward and downward flexibility requirements of node k at time t in a typical scenario s, They are the upward and downward flexibility supply of node k at time t under typical scenario s, respectively; The constraints of the upper-level planning model include pumped storage units and line planning and construction constraints, including: In the above formula, x i The number of pumped storage units added at the hydropower station i, are the upper and lower limits of the number of additional pumped storage units to be built at hydropower station i, l j is the number of newly built lines j, are the upper and lower limits of the number of newly built lines j, is the upper limit of equivalent annual construction and maintenance cost, Π1 is the set of hydropower stations to be built with pumped storage units, and Π2 is the set of lines to be built; The constraints of the lower-level operation model include: power flow balance constraints, line capacity constraints, thermal power output constraints, hydropower output constraints, pumped storage operation constraints, and node voltage phase angle constraints. The formula is as follows: a. Power flow balance constraints: In the above formula, P th,s , P hy,s , P re,s , P load,s They are the output vector of thermal power units, the output vector of hydropower units, the output vector of new energy units, and the node load vector under the typical scenario s. are respectively the pumped storage power generation and pumped hydropower vectors, B is the node admittance matrix, θ s is the node voltage phase angle vector under typical scenario s; b. Line capacity constraints: In the above formula, is the number of line j before expansion, P j ' ,max is the transmission capacity of a single line j; c. Thermal power output constraints d. Hydropower output constraints include hydropower station constraints and hydropower unit constraints; d1. Hydropower station constraints include hydraulic connection constraints, water level constraints, outflow constraints, hydropower station output constraints, water level-reservoir capacity relationship constraints, and tailwater level-discharge relationship constraints: Hydraulic connection constraint: V i,s,t =V i,s,t-1 +3600(I i,s,t -Q i,s,t )Δt; Water level constraints: Outbound traffic constraints: Hydropower station output constraints: Water level-reservoir capacity relationship constraints: Tailwater level-discharge relationship constraints: In the above formula, V i,s,t is the storage capacity of hydropower station i in period t under typical scenario s, I i,s,t is the inflow of hydropower station i in period t under typical scenario s, Q i,s,t is the outflow of hydropower station i in period t under typical scenario s, τ is the water lag time between hydropower station i and its upstream hydropower station i-1, Q i-1,s,t-τ is the outflow of hydropower station i-1 in period t-τ after considering water lag under typical scenario s; R i,s,t is the interval flow between hydropower station i-1 and hydropower station i in period t under typical scenario s, are the pumping and power generation flows of the pumped storage unit i in the typical scenario s, are respectively the power generation and abandoned water flow of hydropower station i in period t under typical scenario s, is the water level in front of the dam of hydropower station i in the reservoir at time period t under typical scenario s, are the upper and lower limits of the water level in front of the dam of the hydropower station i in the reservoir where it is located, is the initial water level during the scheduling period under the typical scenario s, Q i are the upper and lower limits of the outflow flow of hydropower station i, is the output of hydropower station i in period t under typical scenario s, P i hydro are the upper and lower limits of the output of hydropower station i, respectively, and f i zv (·) is the nonlinear relationship curve function between water level and storage capacity of the reservoir where the hydropower station i is located, f i zq (·) is the nonlinear relationship curve function between the tailwater level and discharge flow of hydropower station i, is the tailwater level of hydropower station i in period t under typical scenario s; d2. Hydropower unit constraints include: unit output constraints, unit power flow constraints, unit start-up and shutdown duration constraints, unit output ramp constraints, unit power head constraints, and unit power characteristic constraints: Unit output constraints: Unit power generation flow constraints: Unit start-up and shutdown duration constraints: Unit output ramp constraint: -ΔP i,n ≤P i,n,s,t+1 -P i,n,s,t ≤ΔP i,n ; Unit generating head constraints: Unit power characteristic constraints: In the above formula, u i,n,s,t is the start-up and shutdown state variable of the nth unit of hydropower station i in period t under typical scenario s, u i,n,s,t ∈{0,1};P i,n,s,t is the output of the nth unit of hydropower station i in period t under typical scenario s; P i ,n are the upper and lower limits of the output of the nth unit of the hydropower station i, 1 represents the start state, and 0 represents the shutdown state; N i is the total number of units included in hydropower station i; is the power generation flow of the nth unit of hydropower station i in period t under typical scenario s, are the upper and lower limits of the power generation flow of the nth unit of hydropower station i, respectively; are the startup and shutdown operation variables of the nth unit of hydropower station i in period t under typical scenario s; are the minimum startup and shutdown durations of the nth unit of hydropower station i, respectively; is the maximum number of startup times of the nth unit of hydropower station i during the dispatch period; ΔP i,n is the climbing capacity of the nth unit of the hydropower station i; H i,n,s,t is the generating head of the nth unit of hydropower station i in period t under typical scenario s; is the nonlinear relationship function of output-head-flow of the nth unit of hydropower station i; e. The pumped storage operation constraints: x vp,i,m,s,t +x vg,i,m,s,t ≤1; P vp,min x vp,i,m,s,t ≤P vp,i,m,s,t ≤P vp,max x vp,i,m,s,t ; P vg,min x vg,i,m,s,t ≤P vg,i,m,s,t ≤P vg,max x vg,i,m,s,t； In the above formula, x vp,i,m,s,t 、x vg,i,m,s,t are the pumping and power generation states of the mth pumped storage unit of hydropower station i in the typical scenario s in time period t. When the value is 1, it means it is in this state, and when the value is 0, it means it is not in this state. vp,i,m,s,t , P vg,i,m,s,t are the pumping and generating power of the mth pumped storage unit of hydropower station i in period t under typical scenario s, P vp,min,i,m , P vp,max,i,m , P vg,min,i,m , P vg,max,i,m are the minimum pumping power, maximum pumping power, minimum generating power, and maximum generating power of the mth pumped storage unit of hydropower station i, respectively. vp,i,m,s,t , Q vg,i,m,s,t are the pumping and power generation flows of the mth pumped-storage unit of hydropower station i in period t under typical scenario s, η p , η g are the pumping and power generation efficiencies of a single pumped storage unit, ρ0 and g are the average density of water and gravitational acceleration, respectively, and h i,s is the average water head of hydropower station i under typical scenario s, N pum,i is the number of pumped storage units in hydropower station i; f. Node voltage phase angle constraint: In the above formula, θ k,s,t is the voltage phase angle of node k in period t under typical scenario s, They are the upper and lower limits of the voltage phase angle at node k respectively.

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