A real-time economic operation method for a multi-unit type water, wind and light complementary system based on a hybrid algorithm

Abstract

The application discloses a kind of based on hybrid algorithm's multi-unit type water wind light complementary system real-time economic operation method, first proposes a kind of water turbine efficiency penalty term, to reduce the frequency of unit low efficiency operation, establish the multi-unit type water wind light complementary system short-term economic operation model considering water consumption rate and unit operation efficiency;Subsequently, the solving dimension of model is reduced using multi-type unit coding strategy;Then the start-stop state of multi-type unit is optimized using black-winged kite optimization algorithm, the related parameters of updating population in black-winged kite optimization algorithm are calibrated, and the load distribution between multiple types of units is determined based on the N-H-Q curve of each type of unit;It can be used to solve the problem that the existing technology under wind and light consumption, the units of hydropower station frequently enter the adverse operating area, resulting in the low efficiency of multi-type unit operation.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of short-term economic operation of water, wind and light complementary system, and particularly relates to a real-time economic operation method of multi-unit type water, wind and light complementary system based on a hybrid algorithm. BACKGROUND

[0002] In the multi-unit type short-term economic operation mode of water, wind and light complementary system, after the access of wind and light, the water turbine may have problems such as running through the vibration zone and low power zone for frequent adjustment of wind and light, and the unit operation efficiency is reduced.

[0003] In order to efficiently solve the short-term economic operation of multi-unit type water, wind and light complementary system, the existing research mainly has the following key technologies: 1, constructing a short-term model. In order to better cope with the multi-dimensional uncertainty faced by the multi-unit type water, wind and light complementary system, robust optimization, interval optimization and stochastic optimization have gradually become important methods for short-term scheduling modeling; 2, model solving method. The short-term optimization scheduling model of multi-unit type water, wind and light complementary system is a kind of nonlinear, non-convex, high-dimensional and multi-stage mathematical programming model. The complexity of the model is due to the strong uncertainty of the input, the operation and physical constraints of the power station and the diversified scheduling objectives, which poses a challenge to its efficient solution. In order to efficiently obtain the optimal short-term scheduling strategy, mixed integer linear programming, intelligent optimization algorithm and hybrid optimization algorithm are widely used in solving the short-term optimization scheduling problem of multi-unit type water, wind and light complementary system; 3, operation risk assessment; the risk faced by the short-term scheduling of water, wind and light complementary system mainly includes the risk of frequent adjustment of wind and light by water turbine, which may cause wear and tear and reduce the operation efficiency of the unit. The main idea of related research is: first, construct a risk evaluation index to quantify the risk, and then embed it into the scheduling model to reduce the risk; the above existing technologies have the following disadvantages:

[0004] 1, high optimization dimension, difficult to solve: first, the multiple types of units increase the number of decision variables, resulting in high dimension of the model solution. Secondly, the volatility and randomness of wind and light resources increase the complexity of the optimization scheduling strategy, which needs to consider multiple factors such as the operation efficiency of each unit, water consumption and start-stop cost, etc., which significantly increases the dimension and complexity of the optimization problem, increasing the difficulty of solving; 2, under complementary operation, water turbine may run through the vibration zone and low power zone due to the need for frequent adjustment of wind and light, thereby reducing the operation efficiency of the unit; the current research has not found a specific solution, and it is difficult to simultaneously consider water consumption rate and unit operation efficiency to effectively carry out the short-term economic operation method of multi-unit type water, wind and light complementary system.

[0005] Therefore, it is necessary to design a real-time economic operation method of multi-unit type water, wind and light complementary system based on a hybrid algorithm to solve the above problems. SUMMARY

[0006] The technical problem solved by the present application is to provide a real-time economic operation method of a multi-unit type water-wind-solar complementary system based on a hybrid algorithm, which is used to solve the problem of low operation efficiency of multi-type units caused by frequent entry of units of a water power station into an unfavorable operation area under wind-solar consumption in the prior art.

[0007] To achieve the above technical effects, the technical scheme adopted by the present application is as follows:

[0008] A real-time economic operation method of a multi-unit type water-wind-solar complementary system based on a hybrid algorithm, comprising the following steps:

[0009] S1, establishing a multi-unit type water-wind-solar complementary system short-term economic operation model considering water consumption rate and unit operation efficiency:

[0010] Establishing an objective function:

[0011] ;

[0012] In the formula, is the total water consumption rate of the water power station at t period; a represents the weight corresponding to the water consumption rate; b represents the weight of the unit operation efficiency penalty term;

[0013] Setting constraint conditions:

[0014] Setting physical and dispatching constraints of the reservoir, the water power station and the water-wind-solar complementary system, including minimum start-up and shutdown time length constraints, water balance constraints and reservoir capacity constraints;

[0015] S2, using a multi-type unit coding strategy to process the minimum start-up and shutdown time length constraints, and reducing the solving dimension of the water-wind-solar complementary system short-term economic operation model;

[0016] S3, using a black-winged kite optimization algorithm to solve the water-wind-solar complementary system short-term economic operation model;

[0017] S4, calibrating parameters of the black-winged kite optimization algorithm;

[0018] S5, calculating the short-term economic operation research results of the multi-unit type water-wind-solar complementary system considering water consumption rate and unit operation efficiency.

[0019] Preferably, in step S1, is a unit operation efficiency penalty term at t period, which contains two parts of the number of low-efficiency operation and the total sum below the unit operation efficiency threshold; The calculation method of is as follows:

[0020] ;

[0021] In the formula, is the total number of units in the multi-unit type water, wind and light complementary system; is the running efficiency of the unit at the moment; is the unit running efficiency threshold value; is an indicator function, which takes the value 1 when , and 0 otherwise; b1 is the weight of the total number of units whose running efficiency is lower than the threshold value; b2 is the weight of the total amplitude of the running efficiency lower than the threshold value.

[0022] Preferably, the minimum start-stop time constraint includes:

[0023]

[0024] In the formula, , is the time for which the unit of the type remains on or off; , is the minimum start-stop time of the unit of the type.

[0025] Further, the water balance constraint includes:

[0026] ;

[0027] In the formula, are the initial and final storage capacities of the time period, respectively, with the unit of m 3 ; is the average inflow of the time period, with the unit of m 3 / s; is the time step of the time period;

[0028] The reservoir capacity constraint includes:

[0029] ;

[0030] In the formula, is the final reservoir water level of the time period, with the unit of m; is the water level-storage capacity curve function.

[0031] Further, the constraint condition can set the power generation water head constraint, the water turbine power characteristics, the water level-storage capacity relationship, the tail water level and the outflow and the water turbine output constraint.

[0032] Preferably, in step S2, a multi-type unit coding strategy is used to handle the minimum start-up and shutdown time constraints, reducing the solution dimensionality of the short-term economic operation model of the hydro-wind-solar hybrid system. The specific method is as follows:

[0033] In the short-term economic operation model of a hydro-wind-solar hybrid system, the decision variable Z is determined by the unit start-up and shutdown state variables. Composition, represented as:

[0034] ;

[0035] In the formula, For the first During the scheduling period of the hydroelectric generating units The start / stop status;

[0036] A multi-type unit coding strategy is adopted, transforming the optimization of unit start-up and shutdown status into the optimization of time nodes and the number of units in operation for each type:

[0037] Between two adjacent time points, the number of generating units in operation remains constant, but the time points at which the operating times of different types of generating units change are different; after processing with coding strategies for multiple types of generating units, the coding strategy for the short-term economic operation model of the hydro-wind-solar hybrid system is expressed as:

[0038] ;

[0039] In the formula, The number of periods during which the number of generating units in operation remains constant during the control period; , The first The type of unit in the first Each time point and the number of machines started.

[0040] Preferably, the Black-winged Kite optimization algorithm is used to solve the short-term economic operation model of the hydro-wind-solar hybrid system, including optimizing the start-up and shutdown status of multiple types of generating units in each scheduling period T using the Black-winged Kite optimization algorithm; the specific method is as follows:

[0041] The Black-winged Kite optimization algorithm uses the population as the basic unit during the update process, first generating an initial population;

[0042] Perform population updates:

[0043] ;

[0044] In the formula, It is each type of unit In the The start / stop status of the generation. It is each type of unit In the The start / stop status of the generation; It is the first The start-stop state of the optimal unit; And Is the weight coefficient, which is the weight of the start-stop state of the current unit moving to the optimal start-stop state of the unit and other start-stop states; The fitness weight of the individual ; The population size; r is a random number between 0 and 1.

[0045] The start-stop state of the unit is optimized by the black-winged kite optimization algorithm, the load distribution between multiple types of units is determined based on the unit load characteristic curves of various types of units, and the short-term economic operation research results of the multi-unit type water-wind-solar complementary system considering water consumption rate and unit operation efficiency are calculated.

[0046] Preferably, among the parameters for calibrating the black-winged kite optimization algorithm, the parameters that need to be calibrated include the population size , the maximum number of iterations and the learning parameter, the learning parameter includes the weight of the population moving to the optimal individual and other individuals And .

[0047] Further, the unit load characteristic curve is an N-H-Q curve, and the acquisition method is to query the N-H-Q curve provided in the factory information of the unit, N represents the output, H represents the water head, and Q represents the flow.

[0048] The beneficial effects of the present application are as follows:

[0049] The short-term economic operation research of the water-wind-solar complementary system considers minimizing water consumption rate and avoiding low unit operation efficiency, and a short-term economic operation model of the multi-unit type water-wind-solar complementary system considering water consumption rate and unit operation efficiency is constructed; this method not only realizes the balance of power station water consumption rate and unit operation efficiency, but also effectively handles the continuous start-stop limit of the unit, greatly reduces the number of optimization variables, realizes dimension reduction, and solves the problem of low operation efficiency of multiple types of units in the prior art due to the frequent entry of each unit of the hydropower station into the adverse operation area under wind-solar consumption. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 The flowchart of the present application;

[0051] Figure 2 The running strategy diagram of different types of units in the embodiment of the present application. DETAILED DESCRIPTION

[0052] Embodiment one:

[0053] For example Figure 1As shown, a real-time economic operation method of a multi-unit type water, wind and light complementary system based on a hybrid algorithm, comprising the following steps:

[0054] S1, a multi-unit type water, wind and light complementary system short-term economic operation model considering water consumption rate and unit operation efficiency is established:

[0055] The objective function is established:

[0056] In the complementary operation mode, due to the need to frequently adjust wind power and photovoltaic power generation, the operation mode and power generation efficiency of the hydropower station will change significantly. After the access of wind and light, the operation efficiency of the unit will often be reduced. Therefore, a water turbine unit efficiency penalty term is proposed to reduce the frequency of low-efficiency operation; by preferentially selecting units with higher efficiency for scheduling, the operation efficiency of the entire multi-unit type water, wind and light complementary system can be improved, and the objective function is:

[0057] ;

[0058] In the formula, is the total water consumption rate of the hydropower station at t period; a represents the weight corresponding to the water consumption rate; b represents the weight of the unit operation efficiency penalty term.

[0059] Set the constraint condition:

[0060] Set the physical and scheduling constraints of the reservoir, hydropower station and water, wind and light complementary system, including minimum start-up and shutdown time constraints, water balance constraints and reservoir capacity constraints;

[0061] S2, the minimum start-up and shutdown time constraints are processed by using a multi-type unit coding strategy to reduce the dimension of the water, wind and light complementary system short-term economic operation model;

[0062] S3, the black-winged kite optimization algorithm is used to solve the water, wind and light complementary system short-term economic operation model;

[0063] S4, the parameters of the black-winged kite optimization algorithm are calibrated;

[0064] S5, the short-term economic operation research results of the multi-unit type water, wind and light complementary system considering water consumption rate and unit operation efficiency are calculated.

[0065] Preferably, in step S1, is the unit operation efficiency penalty term at t period, which includes two parts: the number of low-efficiency operation and the total sum below the unit operation efficiency threshold; The calculation method of is as follows:

[0066] ;

[0067] In the formula, is the total number of units in the multi-unit type water, wind and light complementary system. It is the first Taiwanese crew Real-time operational efficiency; It is the unit operating efficiency threshold; It is an indicator function, when The value is 1 when the unit's operating efficiency is below the threshold, and 0 otherwise; b1 is the weight of the total number of units whose operating efficiency is below the threshold; b2 is the weight of the total range of units whose operating efficiency is below the threshold.

[0068] Preferably, the minimum start-up and shutdown duration constraints include:

[0069]

[0070] In the formula: , For the first Type 1 The operating and shutdown times of the unit; , For the first Minimum start-up and shutdown times for each type of unit.

[0071] Furthermore, water balance constraints include:

[0072] ;

[0073] In the formula, They are respectively Initial and final water storage for a given period, in cubic meters (m³). 3 ; for Average inflow rate over a period of time, in m³ 3 / s; for Time step of the period;

[0074] Storage capacity constraints include:

[0075] ;

[0076] In the formula, for Reservoir water level at the end of the time period, in meters; This is a function representing the water level and reservoir capacity curve.

[0077] Furthermore, constraints can also be set for power generation head constraints, hydropower unit dynamic characteristics, water level-reservoir capacity relationship, tailrace water level and outflow, and hydropower unit output constraints.

[0078] Preferably, in step S2, a multi-type unit coding strategy is used to handle the minimum start-up and shutdown time constraints, reducing the solution dimensionality of the short-term economic operation model of the hydro-wind-solar hybrid system. The specific method is as follows:

[0079] In the short-term economic operation model of a hydro-wind-solar hybrid system, the decision variable Z is determined by the unit start-up and shutdown state variables. Composition, represented as:

[0080] ;

[0081] In the formula, For the first During the scheduling period of the hydroelectric generating units The start / stop status;

[0082] The more decision variables there are, the higher the dimensionality of the model, and the more complex the solution. To effectively handle the minimum start-up and shutdown duration constraint, a multi-type unit coding strategy is adopted, transforming the optimization of unit start-up and shutdown states into optimizing time nodes and the number of units of each type in operation.

[0083] Between two adjacent time points, the number of generating units in operation remains constant, but the time points at which the operating times of different types of generating units change are different. After processing with coding strategies for multiple types of generating units, the coding strategy for the short-term economic operation model of the hydro-wind-solar hybrid system is expressed as follows:

[0084] ;

[0085] In the formula, The number of periods during which the number of generating units in operation remains constant during the control period; , The first The type of unit in the first Each time point and the number of machines started.

[0086] Preferably, the Black-winged Kite optimization algorithm is used to solve the short-term economic operation model of the hydro-wind-solar hybrid system, including optimizing the start-up and shutdown status of multiple types of generating units in each scheduling period T using the Black-winged Kite optimization algorithm; the specific method is as follows:

[0087] The Black-winged Kite optimization algorithm uses the population as the basic unit during the update process, first generating an initial population;

[0088] Perform population updates:

[0089] ;

[0090] In the formula, It is each type of unit In the The start / stop status of the generation. It is each type of unit In the The start / stop status of the generation; It is the first The start-up and shutdown status of the optimal unit; and are weight coefficients for the weight of the movement of the start-stop state of the current unit to the optimal start-stop state of the unit and other start-stop states; is the fitness weight of the individual ; is the population size; r is a random number between 0 and 1.

[0091] The start-stop state of the unit is optimized by the black-winged kite optimization algorithm, the load distribution between multiple types of units is determined based on the unit load characteristic curves of various types of units, and the short-term economic operation of the multi-unit type water-wind-solar complementary system considering the water consumption rate and the unit operation efficiency is calculated.

[0092] Preferably, among the parameters of the black-winged kite optimization algorithm, the parameters that need to be calibrated include the population size , the maximum number of iterations, and the learning parameter, the learning parameter includes the weight of the movement of the population to the optimal individual and other individuals and .

[0093] Further, the unit load characteristic curve is an N-H-Q curve, and the acquisition method is to query the N-H-Q curve provided in the factory information of the unit, N represents the output, H represents the water head, and Q represents the flow.

[0094] Embodiment two:

[0095] As shown in the adjacent two time nodes, the number of units in operation is unchanged, avoiding frequent changes in the operation state of the unit, and the time nodes of the operation time changes of multiple types of units can be different. After adopting the multi-type unit coding strategy, the coding strategy of the model is represented as: Figure 2

[0096] ;

[0097] In the formula: is the number of time periods in which the number of units in operation is continuously unchanged within the regulation period; , are the number of the th unit and the number of units in operation at the th time node, respectively;

[0098] For example, for a multi-unit type water-wind-solar complementary system, there are 4 types of units, and the number of units is 2, 2, 3, and 4, respectively, the scheduling period is one day, the calculation step is one hour, 6, after adopting the multi-type unit coding strategy, the number of decision variables can be reduced from 264 to 44.​

Claims

1. A real-time economic operation method for a multi-unit type hydro-wind-solar hybrid system based on a hybrid algorithm, characterized in that, Includes the following steps: S1. Establish a short-term economic operation model for a multi-unit type hydro-wind-solar hybrid system that takes into account both water consumption rate and unit operating efficiency: Establish the objective function: ； In the formula, Let t represent the total water consumption rate of the hydropower station during time period t; a represents the weight corresponding to the water consumption rate; b represents the weight of the unit operating efficiency penalty term. Set constraints: Set physical and scheduling constraints for reservoirs, hydropower stations and hydro-wind-solar hybrid systems, including minimum start-up and shutdown time constraints, water balance constraints and reservoir capacity constraints. The unit operating efficiency penalty item for time period t includes two parts: the number of times the unit operates inefficiently and the total number of times the unit operates below the unit operating efficiency threshold. The calculation method is as follows: ； In the formula, It refers to the total number of generating units in a multi-unit type hydro-wind-solar hybrid system; It is the first Taiwanese crew Real-time operational efficiency; It is the unit operating efficiency threshold; It is an indicator function, when The value is 1 if the unit's operating efficiency is below the threshold, and 0 otherwise; b1 is the weight of the total number of units whose operating efficiency is below the threshold; b2 is the weight of the total range of unit operating efficiency below the threshold. S2 employs a multi-type unit coding strategy to handle minimum start-up and shutdown time constraints, reducing the solution dimensionality of the short-term economic operation model for the hydro-wind-solar hybrid system. The specific method is as follows: In the short-term economic operation model of a hydro-wind-solar hybrid system, the decision variable Z is determined by the unit start-up and shutdown state variables. Composition, represented as: ； In the formula, For the first During the scheduling period of the hydroelectric generating units The start / stop status; A multi-type unit coding strategy is adopted, transforming the optimization of unit start-up and shutdown status into optimization of time nodes and the number of units in operation for each type: Between two adjacent time points, the number of generating units in operation remains constant, but the time points at which the operating times of different types of generating units change are different; after processing with coding strategies for multiple types of generating units, the coding strategy for the short-term economic operation model of the hydro-wind-solar hybrid system is expressed as: ； In the formula, The number of periods during which the number of generating units in operation remains constant during the control period; , The first The type of unit in the first Each time point and the number of machines started; S3. The Black-winged Kite optimization algorithm is used to solve the short-term economic operation model of the water-wind-solar hybrid system. S4 represents the parameters of the optimization algorithm for the black-winged kite. S5, the results of a short-term economic operation study of a multi-unit type hydro-wind-solar hybrid system that takes into account both water consumption rate and unit operating efficiency.

2. The real-time economic operation method for a multi-unit type hydro-wind-solar hybrid system based on a hybrid algorithm according to claim 1, characterized in that, Minimum start-up and shutdown duration constraints include: ； In the formula: , For the first Type 1 The operating and shutdown times of the unit; , For the first Minimum start-up and shutdown times for each type of unit.

3. The real-time economic operation method for a multi-unit type hydro-wind-solar hybrid system based on a hybrid algorithm according to claim 1, characterized in that, The Black-winged Kite Optimization Algorithm is used to solve the short-term economic operation model of the hydro-wind-solar hybrid system. This includes optimizing the start-up and shutdown states of various types of generating units in each scheduling period T using the Black-winged Kite Optimization Algorithm. The specific method is as follows: The Black-winged Kite optimization algorithm uses the population as the basic unit during the update process, first generating an initial population; Perform population updates: ； In the formula, It is each type of unit In the The start / stop status of the generation. It is each type of unit In the The start / stop status of the generation; It is the first The start-up and shutdown status of the optimal unit; and It is a weighting coefficient, used to weigh the current start-stop state of the unit when moving to the optimal start-stop state and other start-stop states. Individual Fitness weights; It is the population size; r is the population size. Random numbers between; The start-up and shutdown status of the units is obtained by optimizing the Black-winged Kite optimization algorithm. Based on the unit load characteristic curves of various types of units, the load distribution among multiple types of units is determined. The short-term economic operation research results of multi-unit type water-wind-solar hybrid system are calculated, taking into account water consumption rate and unit operating efficiency.

4. The real-time economic operation method for a multi-unit type hydro-wind-solar hybrid system based on a hybrid algorithm according to claim 3, characterized in that, Among the parameters that need to be calibrated in the optimization algorithm for black-winged kites, the population size is one of them. The maximum number of iterations and learning parameters, including the weights for moving the population towards the best individual and other individuals. and .

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