Peak regulation scheduling method and device considering refined modeling, equipment and medium

Abstract

The invention relates to the technical field of optimal scheduling of a multi-energy complementary power generation system, in particular to a peak regulation scheduling method, device and equipment considering refined modeling and a medium, and the method comprises the steps: taking the minimum residual load peak-valley difference and the minimum residual load variance as target functions; establishing constraint conditions considering hybrid pumping and storage fine modeling, wherein the constraint conditions comprise a hybrid pumping and storage power station constraint condition considering hydraulic coupling and a constraint condition for processing runoff inflow uncertainty by adopting a discrete scene method; establishing a peak regulation scheduling model considering hybrid pumping and storage refined modeling according to the target function and constraint conditions of refined modeling; a linearization method is adopted to linearize nonlinear constraints related to hybrid pumping and storage in the constraint conditions; and solving the linearized peak regulation scheduling model, and obtaining a scheduling result. According to the method, runoff inflow uncertainty is considered, refined modeling of the hybrid pumped storage power station is closer to reality, and feasibility of a power generation scheme is better guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of optimization scheduling of multi-energy complementary power generation systems, and in particular to a peak-shaving scheduling method, device, equipment and medium taking into account refined modeling. Background Art

[0002] With the rapid development and construction of clean energy and the increasing requirements for safe, stable and economical operation of power grids, the power grid has a huge demand for energy storage facilities. Under the objective condition that other energy storage methods and facilities are currently unable to meet the power grid's requirements for reliability, safety and energy storage capacity, pumped storage power stations are currently the most important means for the power grid to absorb clean energy and ensure safe and stable operation of the power grid. Pumped storage power stations are mature and complete energy storage facilities that have both reliability and safety and energy storage capacity that meets the needs of the power grid. It is imperative to accelerate the construction of pumped storage power stations.

[0003] With the acceleration of the construction of pure pumped storage power stations, the remaining good sites are becoming fewer and fewer, the environmental factors are becoming more and more complex, and the conditions for project development and construction are becoming more and more demanding. The water-storage intermodal development model has been proven to be technically feasible, economically reasonable, and reliable in operation. In addition, the incremental power conversion during the energy storage process is significant, and the comprehensive power conversion efficiency is high. Therefore, it will become a trend to develop and build hybrid pumped storage power stations in combination with conventional cascade hydropower stations as a supplement.

[0004] With the development of economy, the electricity consumption structure has changed. The increase of load peak-valley difference has made the grid operation stability worse. The existing technology on peak regulation and load fluctuation suppression of hybrid pumped storage power stations rarely considers the refined modeling of hybrid pumped storage. Rough modeling will lead to inaccurate optimization scheduling results and affect the feasibility of power generation plan.

[0005] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The present invention provides a peak load scheduling method, device, equipment and medium taking into account refined modeling, thereby effectively solving the problems in the background technology.

[0007] In order to achieve the above object, the technical solution adopted by the present invention is: a peak load scheduling method considering refined modeling, comprising the following steps:

[0008] The objective function is to minimize the peak-to-valley difference of residual load and the variance of residual load;

[0009] Establishing constraints for hybrid pumped storage refinement modeling, including: constraints for hybrid pumped storage power stations considering hydraulic coupling, and constraints for handling runoff water uncertainty using a discrete scenario approach;

[0010] A peak load dispatching model considering hybrid pumped storage refined modeling is established based on the objective function and the constraints of refined modeling;

[0011] A linearization method is used to linearize the nonlinear constraints related to the hybrid pumped storage in the constraint conditions;

[0012] The linearized peak load scheduling model is solved and a scheduling result is obtained.

[0013] Furthermore, the objective function includes:

[0014] J1=P t residual_up -P t residual_low

[0015]

[0016] min J = λ1J1 + λ2J2;

[0017] Where J is the total objective function; J1 and J2 are two objective functions respectively; T is a scheduling period; P t residual is the residual load of the external power grid; P t load is the original load of the external power grid; is the output power of the mth conventional unit in the hydropower station i; and are the generating power and pumping power of the nth pumped storage unit in the hydropower station i, respectively; P t residual_up is the upper limit of the residual load; P t residual_low is the lower bound of the residual load; λ1 and λ2 are weight coefficients.

[0018] Furthermore, the constraints include:

[0019] Hydraulic constraints of hybrid pumped storage power station: flow balance constraints;

[0020] Power-related constraints of hybrid pumped-storage power stations: output constraints of conventional hydropower units, load distribution constraints of units within hybrid pumped-storage power stations, constraints on the relationship between output power and water head and power generation flow, unit power climbing constraints and unit output vibration zone constraints.

[0021] Furthermore, for a hybrid pumped storage power station, the flow balance constraint includes:

[0022]

[0023] Where V i,t is the storage capacity of the i-th reservoir; is the release flow of the i-th hydropower station, and the power generation flow of the hydropower unit Pumped storage unit power flow and the pumping flow of the pumped storage unit and abandoned water The subscript m refers to the mth conventional unit in the hydropower station i, and the subscript n refers to the nth pumped storage unit in the hydropower station i. If there is no pumped storage unit, n is 0; τ ij is the water flow lag between the i-th reservoir and the j-th reservoir;

[0024] For a run-of-river hydropower station, the flow balance constraint is:

[0025]

[0026] In the formula, I i,t It is natural runoff.

[0027] Furthermore, the conventional hydropower unit output constraints include:

[0028]

[0029] Where η i,m is the power generation efficiency of each unit;

[0030] The load distribution constraints of the units in the hybrid pumped storage power station include:

[0031]

[0032] In the formula, is the power of power station i, including the power generation power of m conventional units, the power generation power of n pumped storage units and the pumping power;

[0033] The constraints on the relationship between the output power, the water head and the power generation flow rate include:

[0034]

[0035] In the formula, f i g (·) represents the functional relationship between output power and water head and power generation flow rate; H i,t is the water head of power station i at period t;

[0036] The unit power ramp constraints include:

[0037]

[0038] In the formula, and They are the maximum climbing limits of conventional hydropower units and pumped storage units respectively;

[0039] The unit output vibration zone constraints include:

[0040]

[0041] In the formula, and They are the upper and lower boundaries of the kth vibration zone of unit m in hydropower station i, respectively.

[0042] Furthermore, the linearization method is used to linearize the nonlinear constraints related to the hybrid pumped storage in the constraint conditions, including:

[0043] The McCormick convex envelope relaxation method is used to linearize the output constraints of the conventional hydropower units:

[0044]

[0045] In the formula, and They are the maximum and minimum values ​​of the power generation flow of conventional hydropower units respectively; and are the maximum and minimum values ​​of water head at power station i, respectively;

[0046] The McCormick convex envelope relaxation method is used to linearize the unit output vibration zone constraints:

[0047]

[0048] In the formula, It is a flag variable indicating whether the system is in the allowed operation area; and are the maximum and minimum values ​​of the power in the kth vibration zone segment, respectively.

[0049] Furthermore, the discrete scenario method is used to process the constraints of runoff water uncertainty, including the following steps:

[0050] Add the objective function of discrete scenarios:

[0051]

[0052] In the formula, p s is the occurrence probability of the sth runoff scenario; and is the objective function in the sth scenario;

[0053] Add traffic balance constraints for discrete scenarios:

[0054]

[0055] Where V i,t,s is the storage capacity of the i-th power station under scenario s; I i,t,s is the natural runoff of the ith power station under scenario s; is the discharge flow of the i-th power station under scenario s.

[0056] Furthermore, solving the linearized peak load scheduling model includes:

[0057] The peak-shaving dispatching model is solved by calling the CPLEX solver using Yalmip, and the output of conventional units of the hybrid pumped-storage power station, the output of pumped-storage units of the hybrid pumped-storage power station and the residual load curve after peak-shaving dispatch are obtained.

[0058] The present invention also includes a peak load scheduling device considering refined modeling, using the above method, the device includes:

[0059] The target unit is used to take the minimum peak-to-valley difference of the residual load and the minimum variance of the residual load as the target function;

[0060] A constraint unit is used to establish constraint conditions for hybrid pumped storage refined modeling, wherein the constraint conditions include: constraint conditions for hybrid pumped storage power station considering hydraulic coupling, and constraint conditions for handling uncertainty of runoff water using a discrete scenario method;

[0061] A modeling unit, used to establish a peak-shaving dispatching model considering hybrid pumped storage refined modeling based on the objective function and the constraints of refined modeling;

[0062] A linearization unit, used for linearizing the nonlinear constraints related to the hybrid pumped storage in the constraint conditions by using a linearization method;

[0063] The solving unit is used to solve the linearized peak load scheduling model and obtain a scheduling result.

[0064] The present invention also includes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method described above is implemented.

[0065] The present invention also includes a storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described above is implemented.

[0066] The beneficial effects of the present invention are as follows: in the present invention, the minimum peak-to-valley difference of residual load and the minimum variance of residual load are taken as objective functions, the constraints of the hybrid pumped-storage power station considering hydraulic coupling and the constraints of uncertainty of runoff water inflow handled by the discrete scenario method are taken as constraint conditions, a peak-shaving scheduling model considering the refined modeling of the hybrid pumped-storage power station is established, and finally the model is solved to obtain the optimized scheduling result, which can provide a hybrid pumped-storage power generation scheme that meets the constraints. After comprehensively considering the relevant constraints of the hybrid pumped-storage power station and the uncertainty of reservoir runoff water inflow, the refined modeling of the hybrid pumped-storage power station is closer to reality, and the feasibility of the power generation scheme is better guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 is a flow chart of the method in Example 1;

[0069] Figure 2 It is a structural schematic diagram of the device in Example 1;

[0070] Figure 3 This is the operation structure diagram of the hybrid pumped storage power station in Example 2;

[0071] Figure 4 This is a flow chart of the coordinated control model of the hybrid pumped storage power station in Example 2;

[0072] Figure 5 The result diagram of the hybrid pumped storage combined power, original load and residual load in Example 2;

[0073] Figure 6 This is the output result diagram of the hybrid pumped storage unit in Example 2.

[0074] Figure 7 It is a schematic diagram of the structure of the computer device of the present invention. DETAILED DESCRIPTION

[0075] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0076] like Figure 1 As shown: A peak load scheduling method considering refined modeling includes the following steps:

[0077] The objective function is to minimize the peak-to-valley difference of residual load and the variance of residual load;

[0078] Establish constraints for the refined modeling of hybrid pumped storage, including: constraints for hybrid pumped storage power stations considering hydraulic coupling, and constraints for handling runoff water uncertainty using discrete scenario methods;

[0079] A peak load dispatching model considering hybrid pumped storage refined modeling is established based on the objective function and the constraints of refined modeling.

[0080] The linearization method is used to linearize the nonlinear constraints related to hybrid pumped storage in the constraint conditions;

[0081] The linearized peak load scheduling model is solved and the scheduling results are obtained.

[0082] By taking the minimum peak-to-valley difference of residual load and the minimum variance of residual load as the objective function, taking the constraints of the hybrid pumped-storage power station considering hydraulic coupling and the constraints of runoff water uncertainty handled by the discrete scenario method as constraints, a peak-shaving scheduling model considering the refined modeling of the hybrid pumped-storage power station is established. Finally, the model is solved to obtain the optimized scheduling result, which can give a hybrid pumped-storage power generation scheme that meets the constraints. After comprehensively considering the relevant constraints of the hybrid pumped-storage power station and the uncertainty of reservoir runoff water, the refined modeling of the hybrid pumped-storage power station is closer to reality, and the feasibility of the power generation scheme is better guaranteed.

[0083] In this embodiment, the objective function includes:

[0084] J1=P t residual_up -P t residual_low

[0085]

[0086] min J = λ1J1 + λ2J2;

[0087] Where J is the total objective function; J1 and J2 are two objective functions respectively; T is a scheduling period; P t residual is the residual load of the external power grid; P t load is the original load of the external power grid; is the output power of the mth conventional unit in the hydropower station i; and are the generating power and pumping power of the nth pumped storage unit in the hydropower station i, respectively; P t residual_up is the upper limit of the residual load; P tresidual_low is the lower bound of the residual load; λ1 and λ2 are weight coefficients.

[0088] The constraints include:

[0089] Hydraulic constraints of hybrid pumped storage power station: flow balance constraints;

[0090] Power-related constraints of hybrid pumped-storage power stations: output constraints of conventional hydropower units, load distribution constraints of units within hybrid pumped-storage power stations, constraints on the relationship between output power and water head and power generation flow, unit power climbing constraints and unit output vibration zone constraints.

[0091] For hybrid pumped storage power stations, the flow balance constraints include:

[0092]

[0093] Where V i,t is the storage capacity of the i-th reservoir; is the release flow of the i-th hydropower station, and the power generation flow of the hydropower unit Pumped storage unit power flow and the pumping flow of the pumped storage unit and abandoned water The subscript m refers to the mth conventional unit in the hydropower station i, and the subscript n refers to the nth pumped storage unit in the hydropower station i. If there is no pumped storage unit, n is 0; τ ij is the water flow lag between the i-th reservoir and the j-th reservoir;

[0094] For a run-of-river hydropower station, the flow balance constraint is:

[0095]

[0096] In the formula, I i,t It is natural runoff.

[0097] As a preferred embodiment of the above, conventional hydropower unit output constraints include:

[0098]

[0099] Where η i,m is the power generation efficiency of each unit;

[0100] The load distribution constraints of the units in the hybrid pumped storage power station include:

[0101]

[0102] In the formula, is the power of power station i, including the power generation power of m conventional units, the power generation power of n pumped storage units and the pumping power;

[0103] The constraints on the relationship between output power, water head and power generation flow include:

[0104]

[0105] In the formula, f i g (·) represents the functional relationship between output power and water head and power generation flow rate; H i,t is the water head of power station i at period t;

[0106] The unit power ramp constraints include:

[0107]

[0108] In the formula, and They are the maximum climbing limits of conventional hydropower units and pumped storage units respectively;

[0109] The unit output vibration zone constraints include:

[0110]

[0111] In the formula, and They are the upper and lower boundaries of the kth vibration zone of unit m in hydropower station i, respectively.

[0112] In this embodiment, a linearization method is used to linearize the nonlinear constraints related to the hybrid pumped storage in the constraint conditions, including:

[0113] The McCormick convex envelope relaxation method is used to linearize the output constraints of conventional hydropower units:

[0114]

[0115] In the formula, and They are the maximum and minimum values ​​of the power generation flow of conventional hydropower units respectively; and are the maximum and minimum values ​​of water head at power station i, respectively;

[0116] The McCormick convex envelope relaxation method is used to linearize the unit output vibration zone constraints:

[0117]

[0118] In the formula, It is a flag variable indicating whether the system is in the allowed operation area; and are the maximum and minimum values ​​of the power in the kth vibration zone segment, respectively.

[0119] As a preferred embodiment of the above, a discrete scenario method is used to process the constraint conditions of runoff water uncertainty, including the following steps:

[0120] Add the objective function of discrete scenarios:

[0121]

[0122] In the formula, p s is the occurrence probability of the sth runoff scenario; and is the objective function in the sth scenario;

[0123] Add traffic balance constraints for discrete scenarios:

[0124]

[0125] Where V i,t,s is the storage capacity of the i-th power station under scenario s; I i,t,s is the natural runoff of the ith power station under scenario s; is the discharge flow of the i-th power station under scenario s.

[0126] The linearized peak load scheduling model is solved, including:

[0127] Yalmip is used to call the CPLEX solver to solve the peak-shaving scheduling model, and the output of conventional units in the hybrid pumped-storage power station, the output of pumped-storage units in the hybrid pumped-storage power station and the residual load curve after peak-shaving scheduling are obtained.

[0128] like Figure 2 As shown, this embodiment also includes a peak load scheduling device considering refined modeling, using the above method, the device includes:

[0129] The target unit is used to take the minimum peak-to-valley difference of the residual load and the minimum variance of the residual load as the target function;

[0130] Constraint unit, used to establish constraint conditions for hybrid pumped storage refinement modeling, including: constraint conditions for hybrid pumped storage power station considering hydraulic coupling, and constraint conditions for handling runoff water uncertainty using discrete scenario method;

[0131] A modeling unit, used to establish a peak load dispatching model considering hybrid pumped storage refined modeling based on the objective function and the constraints of refined modeling;

[0132] A linearization unit, used for linearizing the nonlinear constraints related to the hybrid pumped storage in the constraint conditions by using a linearization method;

[0133] The solving unit is used to solve the linearized peak load scheduling model and obtain the scheduling result.

[0134] Embodiment 2:

[0135] In this embodiment, a peak load scheduling method considering the refined modeling of a hybrid pumped storage power station is provided, comprising the following steps:

[0136] 1) Taking the minimum peak-to-valley difference of residual load and the minimum variance of residual load as the objective function;

[0137] 2) Establish the constraints of the peak-shaving dispatching model considering the refined modeling of hybrid pumped storage, including: the constraints of the hybrid pumped storage power station considering hydraulic coupling, and the constraints of handling the uncertainty of runoff water using the discrete scenario method;

[0138] 3) Linearization methods such as McCormick convex envelope relaxation method are used to linearize the nonlinear constraints related to hybrid pumped storage;

[0139] 4) Solving the scheduling model to obtain a scheduling result.

[0140] In this embodiment, the minimum peak-to-valley difference of residual load and the minimum variance of residual load are taken as objective functions, and the constraints of the hybrid pumped-storage power station considering hydraulic coupling and the constraints of uncertainty of runoff water inflow handled by the discrete scenario method are taken as constraint conditions. A peak-shaving scheduling model considering the refined modeling of the hybrid pumped-storage power station is established. Finally, the model is solved to obtain the optimized scheduling result, and a hybrid pumped-storage power generation scheme that meets the constraints can be given. After comprehensively considering the relevant constraints of the hybrid pumped-storage power station and the uncertainty of reservoir runoff water inflow, the refined modeling of the hybrid pumped-storage power station is closer to reality, and the feasibility of the power generation scheme is better guaranteed.

[0141] In this embodiment, the objective function includes:

[0142] The objective function is to minimize the peak-to-valley difference of residual load and the variance of residual load:

[0143] Only minimizing the peak-to-valley difference of the external grid residual load as the objective function will ignore the volatility of the residual load. In order to simultaneously reflect the dual functions of the hybrid pumped storage power station in reducing peak loads and filling valleys and smoothing load fluctuations, the minimum peak-to-valley difference of the residual load and the minimum variance of the residual load are selected as the objective functions.

[0144] J1=P t residual_up -P t residual_low

[0145]

[0146] min J = λ1J1 + λ2J2;

[0147] Where P t residual is the residual load of the external power grid; P t load is the original load of the external power grid; is the output power of the mth conventional unit in the hydropower station i; and are the generating power and pumping power of the nth pumped storage unit in the hydropower station i, respectively; P t residual_up is the upper limit of the residual load; P t residual_low is the lower bound of the residual load; λ1 and λ2 are weight coefficients.

[0148] Hydraulic constraints of hybrid pumped storage power plants include:

[0149] The hybrid pumped storage power generation system is constructed according to the characteristics of hydropower generation, which includes the factors affecting the hydropower generation flow, the coupling relationship between the power generation characteristics of the hydropower resources and the power station water, including the cascade hydropower generation flow, the pumped storage unit generation flow and the pumping flow;

[0150] Traffic balance constraints:

[0151]

[0152] Where V i,t is the storage capacity of the i-th reservoir; is the release flow of the i-th hydropower station, and the power generation flow of the hydropower unit Pumped storage unit power flow and the pumping flow of the pumped storage unit and abandoned water The subscript m refers to the mth conventional unit in the hydropower station i, and the subscript n refers to the nth pumped storage unit in the hydropower station i. If there is no pumped storage unit, n is 0; τ ij is the water flow lag between the i-th reservoir and the j-th reservoir;

[0153] For run-of-river hydropower stations, due to the lack of reservoirs with regulation capabilities, their flow balance constraints are:

[0154]

[0155] In the formula, I i,t It is natural runoff;

[0156] Power-related constraints for hybrid pumped storage include:

[0157] Load distribution constraints of units in hybrid pumped storage power station:

[0158] The combined power output from the hybrid pumped-storage power station to the external grid is composed of the output power of the original cascade power station generator units and the newly installed pumped-storage units. The power transmission direction is reversed under the pumping condition of the pumped-storage units. The load distribution of each unit in the power station includes the power generation power of the conventional hydropower units, the power generation power of the pumped-storage units and the pumping power.

[0159]

[0160] In the formula, is the power of power station i, including the power generation power of m conventional units, the power generation power of n pumped storage units and the pumping power;

[0161] Constraints on the relationship between output power, water head and power generation flow:

[0162] For the refined modeling of hybrid pumped storage power stations, the influence of water head and power generation flow on output power should be considered simultaneously;

[0163]

[0164] In the formula, f i g (·) represents the functional relationship between output power and water head and power generation flow rate; H i,t is the water head of power station i at period t;

[0165] Unit power ramp constraint:

[0166]

[0167] In the formula, and They are the maximum climbing limits of conventional hydropower units and pumped storage units respectively;

[0168] Unit output vibration zone constraints:

[0169]

[0170] In the formula, and They are the upper and lower boundaries of the kth vibration zone of unit m in hydropower station i, respectively.

[0171] A discrete scenario approach is used to handle the constraints of runoff uncertainty, including:

[0172] In reality, the amount of water in a reservoir varies with seasons and time, and its runoff input parameters are uncertain values. The discrete scenario method is used to describe it and increase the accuracy of reservoir runoff water forecasting.

[0173] Add the objective function of discrete scenarios:

[0174]

[0175] In the formula, p s is the occurrence probability of the sth runoff scenario; and is the objective function in the sth scenario;

[0176] Add traffic balance constraints for discrete scenarios:

[0177]

[0178] Where V i,t,s is the storage capacity of the i-th power station under scenario s; I i,t,s is the natural runoff of the ith power station under scenario s; is the discharge flow of the i-th power station under scenario s.

[0179] Nonlinear constrained linearization of hybrid pumped storage, including:

[0180] Linearization of the relationship between conventional hydropower unit output, water head and downstream flow:

[0181] Output constraints of conventional hydropower units:

[0182]

[0183] Where η i,m is the power generation efficiency of each unit;

[0184] The McCormick convex envelope relaxation method is used to linearize the output characteristics of conventional hydropower units:

[0185]

[0186] In the formula, and They are the maximum and minimum values ​​of the power generation flow of conventional hydropower units respectively; and are the maximum and minimum values ​​of water head at power station i, respectively;

[0187] Constrained linearization of unit output vibration zone:

[0188]

[0189] in, It is a flag variable indicating whether the system is in the allowed operation area. and are the maximum and minimum values ​​of the power in the kth vibration zone segment, respectively.

[0190] Specifically, the peak-shaving dispatching model considering the refined modeling of the hybrid pumped-storage power station is solved to obtain a peak-shaving dispatching method of the hybrid pumped-storage power station with refined modeling, including:

[0191] Yalmip is used to call the CPLEX solver to solve the peak-shaving scheduling model considering the refined modeling of the hybrid pumped-storage power station, and the output of the conventional units of the hybrid pumped-storage power station, the output of the pumped-storage units of the hybrid pumped-storage power station and the residual load curve after peak-shaving scheduling are obtained.

[0192] In order to demonstrate the effectiveness of the peak-shaving scheduling method considering the refined modeling of the hybrid pumped-storage power station provided in this embodiment, it is described below in combination with specific application scenarios.

[0193] The embodiment of the present invention is based on the cascade hydropower system of the Jinxi River Basin in Suichang County, Zhejiang Province, which has four hydropower stations, namely Dagongkeng (3.32MW hydropower 1), Chengping Level 1 (13MW hydropower 2), Kuichuan (2.23MW hydropower 3), and Chengping Level 2 (9MW hydropower 4). Dagongkeng and Kuichuan are run-of-river hydropower stations, Chengping Level 1 is an incomplete annual regulation hydropower station, Chengping Level 2 is a seasonal regulation hydropower station, and the second-level hydropower station is equipped with a 5MW variable speed pumped storage unit. The operating structure of the hybrid pumped storage power station is as follows: Figure 3 As shown in the figure, the coordinated control model process of the hybrid pumped storage power station is as follows Figure 4 The specific simulation parameters of the hybrid pumped storage power station are shown in Table 1.

[0194] Table 1 Parameters of hybrid pumped storage power station

[0195]

[0196] First, the objective function of peak load dispatch considering the refined modeling of hybrid pumped storage power station is established as follows:

[0197] J1=P t residual_up -P t residual_low

[0198]

[0199] min J = λ1J1 + λ2J2;

[0200] Among them, P t residual is the residual load of the external power grid; P t load is the original load of the external power grid; is the output power of the mth conventional unit in the hydropower station i; and are the generating power and pumping power of the nth pumped storage unit in the hydropower station i, respectively; Pt residual_up is the upper limit of the residual load; P t residual_low is the lower bound of the residual load; λ1 and λ2 are weight coefficients.

[0201] Then, the hydraulic constraints of the hybrid pumped storage power station are established:

[0202] 1) Traffic balance constraints:

[0203]

[0204] Among them, V i,t is the storage capacity of the i-th reservoir; is the release flow of the i-th hydropower station, and the power generation flow of the hydropower unit Pumped storage unit power flow and the pumping flow of the pumped storage unit and abandoned water The subscript m refers to the mth conventional unit in the hydropower station i, and the subscript n refers to the nth pumped storage unit in the hydropower station i. If there is no pumped storage unit, n is 0; τ ij is the water flow lag between the i-th reservoir and the j-th reservoir;

[0205] 2) For run-of-river hydropower stations, due to the lack of reservoirs with regulation capabilities, their flow balance constraints are:

[0206]

[0207] Among them, I i,t It is natural runoff;

[0208] Then the power-related constraints of hybrid pumped storage are established, including:

[0209] 1) Load distribution constraints of units in hybrid pumped storage power stations:

[0210]

[0211] in, is the power of power station i, including the power generation power of m conventional units, the power generation power of n pumped storage units and the pumping power.

[0212] 2) Constraints on the relationship between output power, water head and power generation flow:

[0213]

[0214] Among them, f i g (·) represents the functional relationship between output power and water head and power generation flow rate; H i,t is the water head of power station i at period t;

[0215] 3) Unit power ramp constraints:

[0216]

[0217]

[0218] in, and They are the maximum climbing limits for conventional hydropower units and pumped storage units respectively.

[0219] 4) Unit output vibration zone constraints:

[0220]

[0221] in, and They are the upper and lower boundaries of the kth vibration zone of unit m in hydropower station i, respectively.

[0222] Then, a discrete scenario method is used to deal with the uncertainty constraints of runoff inflow:

[0223] 1) Add the objective function of discrete scenes:

[0224]

[0225] Among them, p s is the occurrence probability of the sth runoff scenario; and is the objective function in the sth scenario;

[0226] 2) Add traffic balance constraints for discrete scenarios:

[0227]

[0228] Among them, V i,t,s is the storage capacity of the i-th power station under scenario s; I i,t,s is the natural runoff of the ith power station under scenario s; is the discharge flow of the i-th power station under scenario s.

[0229] Then the nonlinear constraints of the hybrid pumped storage are linearized:

[0230] 1) Linearization of the relationship between conventional hydropower unit output, water head and downstream flow:

[0231] Output constraints of conventional hydropower units:

[0232]

[0233] Among them, η i,m is the power generation efficiency of each unit;

[0234] The McCormick convex envelope relaxation method is used to linearize the output characteristics of conventional hydropower units:

[0235]

[0236] in, and They are the maximum and minimum values ​​of the power generation flow of conventional hydropower units respectively; and are the maximum and minimum values ​​of water head at power station i, respectively;

[0237] 2) Linearization of unit output vibration zone constraints:

[0238]

[0239] in, It is a flag variable indicating whether the system is in the allowed operation area; and are the maximum and minimum values ​​of the power in the kth vibration zone segment, respectively.

[0240] Finally, Yalmip is used to call the CPLEX solver to solve the peak-shaving scheduling model considering the refined modeling of the hybrid pumped storage power station, and the peak-shaving scheduling scheme considering the refined modeling of the hybrid pumped storage power station is obtained. Figure 5 and Figure 6 The peak regulation and combined output results of the hybrid pumped-storage power station and the unit output results of the hybrid pumped-storage power station are shown respectively.

[0241] See also Figure 7 A computer device 400 provided in an embodiment of the present application includes: a processor 410 and a memory 420, wherein the memory 420 stores a computer program executable by the processor 410, and when the computer program is executed by the processor 410, the above method is executed.

[0242] The embodiment of the present application further provides a storage medium 430 on which a computer program is stored. When the computer program is run by the processor 410, the above method is executed.

[0243] Among them, the storage medium 430 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, disk or optical disk.

[0244] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0245] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0246] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0247] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0248] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0249] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0250] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0251] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present invention.

Claims

1. A peak load scheduling method considering refined modeling, characterized in that: The steps include: The objective function is to minimize the peak-to-valley difference of residual load and the variance of residual load; Establishing constraints for hybrid pumped storage refinement modeling, including: constraints for hybrid pumped storage power stations considering hydraulic coupling, and constraints for handling runoff water uncertainty using a discrete scenario approach; A peak load dispatching model considering hybrid pumped storage refined modeling is established based on the objective function and the constraints of refined modeling; A linearization method is used to linearize the nonlinear constraints related to the hybrid pumped storage in the constraint conditions; The linearized peak load scheduling model is solved and a scheduling result is obtained.

2. The peak load scheduling method considering refined modeling according to claim 1 is characterized in that: The objective function includes: J1=P t residual_up -P t residual_low min J = λ1J1 + λ2J2; Where J is the total objective function; J1 and J2 are two objective functions respectively; T is a scheduling period; P t residual is the residual load of the external power grid; P t load is the original load of the external power grid; is the output power of the mth conventional unit in the hydropower station i; and are the generating power and pumping power of the nth pumped storage unit in the hydropower station i, respectively; P t residual_up is the upper limit of the residual load; P t residual_low is the lower bound of the residual load; λ1 and λ2 are weight coefficients.

3. The peak load scheduling method considering refined modeling according to claim 1 is characterized in that: The constraints include: Hydraulic constraints of hybrid pumped storage power station: flow balance constraints; Power-related constraints of hybrid pumped-storage power stations: output constraints of conventional hydropower units, load distribution constraints of units within hybrid pumped-storage power stations, constraints on the relationship between output power and water head and power generation flow, unit power climbing constraints and unit output vibration zone constraints.

4. The peak load scheduling method considering refined modeling according to claim 3 is characterized in that: For a hybrid pumped storage power station, the flow balance constraints include: Where V i,t is the storage capacity of the i-th reservoir; is the release flow of the i-th hydropower station, and the power generation flow of the hydropower unit Pumped storage unit power flow and the pumping flow of the pumped storage unit and abandoned water The subscript m refers to the mth conventional unit in the hydropower station i, and the subscript n refers to the nth pumped storage unit in the hydropower station i. If there is no pumped storage unit, n is 0; τ ij is the water flow lag between the i-th reservoir and the j-th reservoir; For a run-of-river hydropower station, the flow balance constraint is: In the formula, I i,t It is natural runoff.

5. The peak load scheduling method considering refined modeling according to claim 3 is characterized in that: The conventional hydropower unit output constraints include: Where η i,m is the power generation efficiency of each unit; The load distribution constraints of the units in the hybrid pumped storage power station include: In the formula, is the power of power station i, including the power generation power of m conventional units, the power generation power of n pumped storage units and the pumping power; The constraints on the relationship between the output power, the water head and the power generation flow rate include: In the formula, f i g (·) represents the functional relationship between output power and water head and power generation flow; H i,t is the water head of power station i at period t; The unit power ramp constraints include: In the formula, and They are the maximum climbing limits of conventional hydropower units and pumped storage units respectively; The unit output vibration zone constraints include: In the formula, and They are the upper and lower boundaries of the kth vibration zone of unit m in hydropower station i, respectively.

6. The peak load scheduling method considering refined modeling according to claim 5 is characterized in that: The linearization method is used to linearize the nonlinear constraints related to the hybrid pumped storage in the constraint conditions, including: The McCormick convex envelope relaxation method is used to linearize the output constraints of the conventional hydropower units: In the formula, and They are the maximum and minimum values ​​of the power generation flow of conventional hydropower units respectively; and are the maximum and minimum values ​​of water head at power station i, respectively; The McCormick convex envelope relaxation method is used to linearize the unit output vibration zone constraints: In the formula, It is a flag variable indicating whether the system is in the allowed operation area. and are the maximum and minimum values ​​of the power in the kth vibration zone segment, respectively.

7. The peak load scheduling method considering refined modeling according to claim 1 is characterized in that: The discrete scenario method is used to deal with the constraints of runoff water uncertainty, including the following steps: Add the objective function of discrete scenarios: In the formula, p s is the occurrence probability of the sth runoff scenario; and is the objective function in the sth scenario; Add traffic balance constraints for discrete scenarios: Where V i,t,s is the storage capacity of the i-th power station under scenario s; I i,t,s is the natural runoff of the ith power station under scenario s; is the discharge flow of the i-th power station under scenario s.

8. The peak load scheduling method considering refined modeling according to claim 1 is characterized in that: Solving the linearized peak load scheduling model includes: The peak-shaving dispatching model is solved by calling the CPLEX solver using Yalmip, and the output of conventional units of the hybrid pumped-storage power station, the output of pumped-storage units of the hybrid pumped-storage power station and the residual load curve after peak-shaving dispatch are obtained.

9. A peak load scheduling device considering refined modeling, characterized in that: Using the method according to any one of claims 1 to 8, the device comprises: The target unit is used to take the minimum peak-to-valley difference of the residual load and the minimum variance of the residual load as the target function; A constraint unit is used to establish constraint conditions for hybrid pumped storage refined modeling, wherein the constraint conditions include: constraint conditions for hybrid pumped storage power station considering hydraulic coupling, and constraint conditions for handling uncertainty of runoff water using a discrete scenario method; A modeling unit, used to establish a peak-shaving dispatching model considering hybrid pumped storage refined modeling based on the objective function and the constraints of refined modeling; A linearization unit, used for linearizing the nonlinear constraints related to the hybrid pumped storage in the constraint conditions by using a linearization method; The solving unit is used to solve the linearized peak load scheduling model and obtain a scheduling result.

10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

11. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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