Multi-objective optimization configuration method of wind-light-fire-pumping storage hybrid power generation system

Abstract

The invention relates to the technical field of hybrid power generation system optimization configuration, in particular to a multi-objective optimization configuration method for a wind-light-fire-pumping storage hybrid power generation system, which comprises the following steps: S10, establishing an objective function including minimum investment cost, maximum transfer channel utilization rate and minimum transfer curve peak-valley difference; s20, constraint conditions of pumping and storage operation constraint, wind and light output constraint and thermal power output constraint are established; s30, normalizing each sub-target in the target function into a single target, and constructing a capacity optimization model of the wind-light-fire-pumped storage hybrid power generation system according to the target function and the constraint condition; and S40, solving the mixed integer linear programming model, and obtaining the multi-objective optimal configuration method of the wind-light-fire-pumped storage hybrid power generation system. By means of the arrangement, the substitutability of the pumped storage unit to the thermal power unit can be fully considered, the utilization rate of new energy is increased, and the multi-target optimization algorithm is adopted to achieve optimal configuration of the hybrid power generation system.

Description

Technical Field

[0001] The present invention relates to the technical field of hybrid power generation system optimization configuration, and in particular to a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system. Background Art

[0002] At present, traditional thermal power generation is gradually being replaced by cleaner and more environmentally friendly new energy generation. However, the penetration rate of new energy poses a huge challenge to the stability of the power grid. Therefore, energy storage equipment is introduced into the system to smooth the fluctuation of new energy output power and ensure the safety of access to the power grid. Pumped storage has the advantages of adjustable flexibility, mature technology, and environmental friendliness, and is considered to be the most mature energy storage method at present. At the same time, the introduction of thermal power units can provide the necessary inertial support for the new energy system.

[0003] In the related technologies, domestic and foreign scholars have conducted a lot of research on the optimal capacity allocation of energy storage systems and the availability of new energy hybrid systems, but most of the research focuses more on the regulation of thermal power or energy storage devices on the output of new energy. Since thermal power is subject to strict policy restrictions, it is urgent for technicians in this field to study the coordinated configuration of pumped storage and thermal power capacity, as well as the replacement of some thermal power units in the system with pumped storage units. Summary of the invention

[0004] In view of at least one of the above technical problems, the present invention provides a multi-objective optimization configuration method for a wind-solar-thermal-pumped-storage hybrid power generation system, which fully considers the substitutability of pumped-storage units for thermal power units, improves the utilization rate of new energy, takes into account economy, and adopts a multi-objective optimization algorithm to achieve the optimal configuration of the hybrid power generation system.

[0005] According to a first aspect of the present invention, a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system is provided, comprising the following steps:

[0006] S10: Establishing an objective function including minimizing investment cost, maximizing transportation channel utilization, and minimizing the peak-to-valley difference of the transportation curve;

[0007] S20: Establish constraints on pumped storage operation, wind and solar power output, and thermal power output;

[0008] S30: normalizing each sub-objective in the objective function into a single objective, and constructing a capacity optimization model of a wind-solar-thermal-pumped storage hybrid power generation system based on the objective function and constraint conditions;

[0009] S40: Solve the mixed integer linear programming model to obtain a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system.

[0010] In some embodiments of the present invention, the calculation formula for minimizing the investment cost is:

[0011]

[0012] Among them, min F1 is the minimum investment cost; IC system Initial cost for equipment purchase and installation; AC system is the annual cost; r is the depreciation coefficient; T a for the entire life cycle of the hybrid power generation system.

[0013] In some embodiments of the present invention, the calculation formula for maximizing the utilization rate of the delivery channel is:

[0014]

[0015] Among them, max F2 is the maximum utilization rate of the transportation channel, P t out is the system transmission power in period t; P L is the maximum capacity of the transmission channel; T is the scheduling period.

[0016] In some embodiments of the present invention, the calculation formula for minimizing the peak-to-valley difference of the conveying curve is:

[0017]

[0018] Among them, min F3 is the minimum peak-to-valley difference of the conveying curve, is the maximum power transmission of the system; is the minimum power transmission of the system.

[0019] In some embodiments of the present invention, the pumped storage operation constraint includes a pumped storage capacity constraint, a pumped storage power constraint and a pumped storage state constraint, and the pumped storage capacity constraint is:

[0020]

[0021] Among them, V t up is the water level of the upper reservoir during period t; and are the pumping flow and power generation flow of pumped storage in period t respectively; and are the highest and lowest water levels of the upper reservoir, respectively; is the final water level of the upper reservoir during the dispatching period, and T is the total number of time periods in the dispatching period.

[0022] In some embodiments of the present invention, the pumped storage power constraint is:

[0023]

[0024] in, and are the flow rates of pumped storage used for power generation and pumping in period t, respectively; and are the generating power and pumping power of the pumped storage in period t respectively; and are power generation and pumping efficiency respectively; wp is the channel transmission efficiency; and are the conversion coefficients under power generation and pumping conditions, respectively; h is the water head height; ρ is the medium density of the pumped storage power station; g is the gravitational acceleration; and are the power generation state and pumping state of the pumped storage in period t respectively; and are the minimum power generation and the maximum power generation respectively; and are the minimum pumping power and the maximum pumping power respectively;

[0025] The pumping state constraint is:

[0026]

[0027] Where N is the number of pumped storage units.

[0028] In some embodiments of the present invention, the wind and solar power output constraint is:

[0029]

[0030] Among them, C w is the total installed capacity of wind turbines; Refers to the maximum installed capacity of wind turbines subject to natural constraints; C pv is the total installed capacity of photovoltaic cells; is the maximum installed capacity of photovoltaic cells; P t w is the output power of the wind turbine in period t; P t pv is the output power of the photovoltaic cell in period t; w,t and δ pv,t are the output coefficients of wind power and photovoltaic power generation, respectively; is the maximum output power of the wind turbine in period t; is the maximum output power of the photovoltaic cell in period t.

[0031] In some embodiments of the present invention, the thermal power output constraint includes a thermal power ramp constraint, a thermal power power constraint, and a transmission channel constraint, wherein:

[0032] The thermal power ramping constraint is:

[0033]

[0034] in, and are the lower and upper limits of the thermal power unit’s climbing capacity respectively; P t th is the output power of the thermal power unit in period t; is the output power of the thermal power unit in the t-1 period; the thermal power constraint is:

[0035]

[0036] in, and are the maximum output power and minimum output power of the thermal power unit respectively;

[0037] The transmission channel constraint is:

[0038]

[0039] Among them, P t out is the power transmission of the system in period t; P L is the maximum capacity of the conveying channel; and are the generating power and pumping power of the pumped storage in period t respectively.

[0040] In some embodiments of the present invention, in step S30, the following steps are included:

[0041] The capacity optimization model of the solar-thermal-pumped storage hybrid power generation system includes:

[0042] After normalizing each sub-goal, marking the investment cost of the hybrid system, and establishing the investment cost value of the hybrid system under different capacity configuration schemes, the aggregation matrix M R for:

[0043]

[0044] Among them, R m,n is the investment cost value of the hybrid system under a certain capacity configuration scheme;

[0045] After normalization, the investment cost of the system can be expressed as:

[0046]

[0047] Finally, the objective function can be calculated as:

[0048]

[0049] α+β+γ=1.

[0050] Among them, f1 * , and are the normalized system sub-objective functions; max(M R ) is the maximization aggregation matrix; maxf is the single objective function transformed from maximizing each sub-objective; α, β and γ are the weight coefficients of each sub-objective respectively.

[0051] In some embodiments of the present invention, in step S40, the following steps are included:

[0052] The mixed integer linear programming model is solved by calling the Gurobi solver using Yalmip. By setting a wind-solar-thermal hybrid power generation system and a wind-solar-thermal-pumped storage hybrid power generation system for comparison, the optimal configuration result of the wind-solar-thermal hybrid power generation system is obtained.

[0053] The beneficial effects of the present invention are as follows: the multi-objective optimization configuration method of a wind-solar-thermal-pumped-storage hybrid power generation system provided by the present invention can fully consider the substitutability of pumped-storage units for thermal power units, improve the utilization rate of new energy, take into account economy, adopt a multi-objective optimization algorithm, and achieve the optimal configuration of the hybrid power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] 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.

[0055] Figure 1 It is a flowchart of the steps of the multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system in an embodiment of the present invention;

[0056] Figure 2 This is a diagram showing the output results of a wind-solar-thermal-pumped storage hybrid power generation system in an embodiment of the present invention;

[0057] Figure 3 This is a diagram showing the output results of a wind-solar-thermal hybrid power generation system in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] 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.

[0059] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0061] like Figures 1 to 3 The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system shown includes the following steps:

[0062] S10: Establishing an objective function including minimizing investment cost, maximizing transportation channel utilization, and minimizing the peak-to-valley difference of the transportation curve;

[0063] S20: Establish constraints mainly based on pumped storage operation constraints, wind and solar power output constraints, and thermal power output constraints;

[0064] S30: normalizing each sub-objective in the objective function into a single objective, and constructing a capacity optimization model of a wind-solar-thermal-pumped storage hybrid power generation system based on the objective function and constraint conditions;

[0065] S40: Solve the mixed integer linear programming model to obtain a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system.

[0066] In the above embodiment, by providing a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system, it is possible to fully consider the substitutability of pumped storage units for thermal power units, improve the utilization rate of new energy, take into account economy, adopt a multi-objective optimization algorithm, and achieve optimal configuration of the hybrid power generation system.

[0067] Specifically, an objective function is established that includes minimizing investment costs, maximizing the utilization of the transportation channel, and minimizing the peak-to-valley difference of the transportation curve, including:

[0068]

[0069] Among them, IC system Initial cost for equipment purchase and installation; AC system is the annual cost; r is the depreciation coefficient; T a for the entire life cycle of the hybrid power generation system;

[0070]

[0071] Among them, P t out is the system transmission power in period t; P L is the maximum capacity of the transport channel; T is the scheduling period;

[0072]

[0073] in, is the maximum power transmission of the system; is the minimum power transmission of the system.

[0074] Specifically, the constraints mainly based on pumped storage operation constraints, wind and solar power output constraints, and thermal power output constraints are established, including:

[0075] Pumped storage capacity constraints:

[0076]

[0077] Among them, V t up is the water level of the upper reservoir during period t; and are the pumping flow and power generation flow of pumped storage in period t respectively; and are the highest and lowest water levels of the upper reservoir, respectively; is the final water level of the upper reservoir during the scheduling period; T is the total number of time periods in the scheduling period.

[0078] Pumped storage power constraints:

[0079]

[0080] in, and are the flow rates of pumped storage used for power generation and pumping in period t, respectively; and are the generating power and pumping power of the pumped storage in period t respectively; and are power generation and pumping efficiency respectively; wp is the channel transmission efficiency; and are the conversion coefficients under power generation and pumping conditions, respectively; h is the water head height; ρ is the medium density of the pumped storage power station; g is the gravitational acceleration; and are the power generation state and pumping state of the pumped storage in period t respectively; and are the minimum power generation and the maximum power generation respectively; and are the minimum pumping power and the maximum pumping power respectively;

[0081] Pumping state constraints:

[0082]

[0083] Where N is the number of pumped storage units;

[0084] Wind and solar power output constraints:

[0085]

[0086] Among them, C w is the total installed capacity of wind turbines; Refers to the maximum installed capacity of wind turbines subject to natural constraints; C pv is the total installed capacity of photovoltaic cells; is the maximum installed capacity of photovoltaic cells; P t w is the output power of the wind turbine in period t; P t pv is the output power of the photovoltaic cell in period t; w,t and δ pv,t are the output coefficients of wind power and photovoltaic power generation, respectively; is the maximum output power of the wind turbine in period t; is the maximum output power of the photovoltaic cell in period t;

[0087] Thermal power ramp constraints:

[0088]

[0089] in, and are the lower and upper limits of the thermal power unit’s climbing capacity respectively; P t th is the output power of the thermal power unit in period t; is the output power of the thermal power unit in the period t-1;

[0090] Thermal power constraints:

[0091]

[0092] in, and are the maximum output power and minimum output power of the thermal power unit respectively;

[0093] Transmission channel constraints:

[0094]

[0095] Among them, P t out is the power transmission of the system in period t; P L The capacity of the transmission channel is limited; and are the generating power and pumping power of the pumped storage in period t respectively.

[0096] The specific parameters of thermal power units and pumped storage units are shown in Table 1:

[0097] Table 1 System operating parameters

[0098]

[0099] Specifically, each sub-objective in the objective function is normalized into a single objective, and a capacity optimization model of a wind-solar-thermal-pumped storage hybrid power generation system is constructed based on the objective function and constraint conditions, including:

[0100] After normalizing each sub-goal, marking the investment cost of the hybrid system, and establishing the investment cost value of the hybrid system under different capacity configuration schemes, the aggregation matrix M R for:

[0101]

[0102] Among them, R m,n is the investment cost value of the hybrid system under a certain capacity configuration scheme;

[0103] After normalization, the investment cost of the system can be expressed as:

[0104]

[0105] Finally, the objective function can be calculated as:

[0106]

[0107] α+β+γ=1

[0108] Among them, f1 * , and are the normalized system sub-objective functions; max(M R) is the maximization aggregation matrix; maxf is the single objective function transformed from maximizing each sub-objective; α, β and γ are the weight coefficients of each sub-objective respectively.

[0109] Specifically, the mixed integer linear programming model is solved to obtain a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system, including:

[0110] The mixed integer linear programming model is solved by calling the Gurobi solver using Yalmip. By setting a wind-solar-thermal hybrid power generation system and a wind-solar-thermal-pumped storage hybrid power generation system for comparison, the optimal configuration result of the wind-solar-thermal hybrid power generation system is obtained.

[0111] When the hybrid system includes two reversible turbine pump units and a thermal power unit with a single unit capacity of 300MW, the capacity optimization configuration results are shown in Table 2:

[0112] Table 2 Optimal configuration results of wind-solar-thermal-pumped storage hybrid system (WPTP)

[0113]

[0114] In order to analyze the role of pumped storage in the hybrid system, a wind-solar-thermal power generation hybrid system is taken as an example. The pumped storage unit is replaced by a thermal power unit, and the capacity optimization configuration results are shown in Table 3:

[0115] Table 3 Optimization configuration results of wind-solar-thermal hybrid power generation system (WPT)

[0116]

[0117] As can be seen from Table 2-3, when pumped storage is added to the system, the installed capacity of wind power and photovoltaic power will increase to a certain extent. Compared with thermal power units, pumped storage has the ability of two-way regulation. Therefore, replacing thermal power with pumped storage of the same capacity can increase the consumption of new energy. At the same time, the comparison of the levelized energy cost, carbon emissions per unit of electricity, and transmission channel utilization of the two hybrid systems is shown in Table 4:

[0118] Table 4 Index comparison

[0119]

[0120] In Table 4, the levelized energy cost of WPTP is 0.029 USD / kWh, which is higher than that of WPT, mainly because the power generation efficiency of pumped storage units is lower than that of pumping. However, since pumped storage power stations do not emit carbon dioxide during the power generation process, while thermal power plants produce a large amount of carbon emissions. In terms of transmission channel utilization, the two are basically the same.

[0121] The output of the wind-solar-thermal-pumped storage hybrid power generation system is as follows: Figure 2 As shown in Figure 2, the wind-solar-thermal hybrid power generation system is Figure 3 Compared with the wind-solar-thermal-pumped storage hybrid power generation system, the wind-solar-thermal hybrid power generation system has insufficient output power during the 6:00 period due to the reduction of wind power and photovoltaic installed capacity.

[0122] Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system, characterized in that: The following steps are involved: S10: Establishing an objective function including minimizing investment cost, maximizing transportation channel utilization, and minimizing the peak-to-valley difference of the transportation curve; S20: Establish constraints on pumped storage operation, wind and solar power output, and thermal power output; S30: normalizing each sub-objective in the objective function into a single objective, and constructing a capacity optimization model of a wind-solar-thermal-pumped storage hybrid power generation system based on the objective function and constraint conditions; S40: Solve the mixed integer linear programming model to obtain a multi-objective optimization configuration method for a wind-solar-thermal-pumped storage hybrid power generation system.

2. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 1 is characterized in that: The calculation formula for minimizing the investment cost is: Among them, min F1 is the minimum investment cost; IC system Initial cost for equipment purchase and installation; AC system is the annual cost; r is the depreciation coefficient; T a for the entire life cycle of the hybrid power generation system.

3. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 2 is characterized in that: The calculation formula for maximizing the utilization rate of the transport channel is: Among them, max F2 is the maximum utilization rate of the transportation channel, P t out is the system transmission power in period t; P L is the maximum capacity of the transmission channel; T is the scheduling period.

4. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 3 is characterized in that: The calculation formula for minimizing the peak-to-valley difference of the conveying curve is: Among them, min F3 is the minimum peak-to-valley difference of the conveying curve, is the maximum power transmission of the system; is the minimum power transmission of the system.

5. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 1 is characterized in that: The pumped storage operation constraints include pumped storage capacity constraints, pumped storage power constraints and pumped storage state constraints. The pumped storage capacity constraints are: Among them, V t up is the water level of the upper reservoir during period t; and are the pumping flow and power generation flow of pumped storage in period t respectively; and are the highest and lowest water levels of the upper reservoir, respectively; is the final water level of the upper reservoir during the dispatching period, and T is the total number of time periods in the dispatching period.

6. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 5 is characterized in that: The pumped storage power constraint is: in, and are the flow rates of pumped storage used for power generation and pumping in period t, respectively; and are the generating power and pumping power of the pumped storage in period t respectively; and are power generation and pumping efficiency respectively; wp is the channel transmission efficiency; and are the conversion coefficients under power generation and pumping conditions, respectively; h is the water head height; ρ is the medium density of the pumped storage power station; g is the gravitational acceleration; and are the power generation state and pumping state of the pumped storage in period t respectively; and are the minimum power generation and the maximum power generation respectively; and are the minimum pumping power and the maximum pumping power respectively; The pumping state constraint is: Where N is the number of pumped storage units.

7. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 1 is characterized in that: The wind and solar output constraints are: Among them, C w is the total installed capacity of wind turbines; Refers to the maximum installed capacity of wind turbines subject to natural constraints; C pv is the total installed capacity of photovoltaic cells; is the maximum installed capacity of photovoltaic cells; is the output power of the wind turbine in period t; is the output power of the photovoltaic cell in period t; w,t and δ pv,t are the output coefficients of wind power and photovoltaic power generation, respectively; is the maximum output power of the wind turbine in period t; is the maximum output power of the photovoltaic cell in period t.

8. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 7 is characterized in that: The thermal power output constraints include thermal power ramp constraints, thermal power power constraints and transmission channel constraints, among which: The thermal power ramping constraint is: in, and They are the lower and upper limits of the climbing of thermal power units respectively; is the output power of the thermal power unit in period t; is the output power of the thermal power unit in the period t-1; The thermal power constraint is: in, and are the maximum output power and minimum output power of the thermal power unit respectively; The transmission channel constraint is: in, is the power transmission of the system in period t; P L is the maximum capacity of the conveying channel; and are the generating power and pumping power of the pumped storage in period t respectively.

9. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 1, characterized in that: In step S30, the following steps are included: The capacity optimization model of the solar-thermal-pumped storage hybrid power generation system includes: After normalizing each sub-goal, marking the investment cost of the hybrid system, and establishing the investment cost value of the hybrid system under different capacity configuration schemes, the aggregation matrix M R for: Among them, R m,n is the investment cost value of the hybrid system under a certain capacity configuration scheme; After normalization, the investment cost of the system can be expressed as: Finally, the objective function can be calculated as: α+β+γ=1; Among them, f1 * 、f2 * and f3 * are the normalized system sub-objective functions; max(M R ) is the maximum aggregation matrix; maxf is the single objective function transformed from maximizing each sub-objective; α, β and γ are the weight coefficients of each sub-objective respectively.

10. The multi-objective optimization configuration method of the wind-solar-thermal-pumped storage hybrid power generation system according to claim 1, characterized in that: In step S40, the following steps are included: The mixed integer linear programming model is solved by calling the Gurobi solver using Yalmip. By setting a wind-solar-thermal hybrid power generation system and a wind-solar-thermal-pumped storage hybrid power generation system for comparison, the optimal configuration result of the wind-solar-thermal hybrid power generation system is obtained.

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