New energy consumption power supply method based on multi-region interconnection

Abstract

The invention discloses a new energy consumption power supply method based on multi-region interconnection, and relates to the technical field of new energy consumption, and the method specifically comprises the steps: 1, building a target function with the minimization of the power generation cost of a power system as a target, and constructing a multi-region interconnection power system model, the model comprises a target function, an electric power balance constraint, a transmission power constraint and a conventional power generation constraint, 2, adjusting the conventional power generation of each region and the transmission power between the regions, maximizing the utilization rate of the new energy, and optimizing the new energy consumption. Step 2, adjusting conventional generating capacity of each region and inter-region transmission power based on a Lagrangian function optimization algorithm, and maximizing new energy consumption, step 3, optimizing generating cost and transmission cost by dynamically adjusting new energy generating capacity, load demand and transmission power of each region, and maximizing new energy consumption. According to the invention, through multi-region interconnection model construction, new energy consumption optimization and real-time adjustment, efficient consumption of new energy is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy consumption, and specifically relates to a new energy consumption and power supply method based on multi-region interconnection. Background Art

[0002] With the rapid development of new energy (such as wind power, solar energy, etc.), the proportion of new energy power generation in the power system has gradually increased. However, the intermittent and volatile nature of new energy power generation has brought challenges to the stable operation of the power system. Traditional power system dispatching methods are difficult to effectively absorb new energy, resulting in serious wind and solar power abandonment. Therefore, how to achieve efficient absorption of new energy through multi-regional interconnection has become an important research direction for current power system dispatching.

[0003] Although multi-regional interconnection provides a new approach to solving the problem of new energy consumption, existing technologies still have the following limitations: traditional dispatching models are mainly designed for conventional energy, which makes it difficult to effectively deal with the volatility and uncertainty of new energy generation; existing dispatching methods are mostly based on offline calculations, which makes it difficult to achieve real-time matching of new energy generation and load demand; existing methods often ignore the economy of the system when optimizing new energy consumption, resulting in high operating costs.

[0004] Therefore, it is urgent to propose a new energy consumption and power supply method based on multi-regional interconnection. By building a multi-regional interconnection model, optimizing new energy consumption, real-time scheduling and economic evaluation, the efficient consumption of new energy and the stable operation of the power system are achieved. Summary of the invention

[0005] The purpose of the present invention is to provide a new energy consumption and power supply method based on multi-region interconnection, which is used to solve the technical problems of single scheduling model, insufficient real-time performance and poor economy in the prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: The new energy consumption and power supply method based on multi-regional interconnection includes: Step 1: Establish an objective function with the goal of minimizing the power generation cost of the power system and construct a multi-regional interconnected power system model; Determine the regional information constituting the power system model, wherein the model includes an objective function determined by the regional information, a power balance constraint, a transmission power constraint, and a conventional power generation constraint; Step 2: Adjust the conventional power generation of each region and the transmission power between regions to maximize the utilization rate of new energy and optimize the consumption of new energy; Taking maximizing the consumption of new energy as the objective function of optimizing the consumption of new energy, the conventional power generation in each region and the transmission power between regions are adjusted based on the Lagrangian function optimization algorithm; Step 3: Optimize power generation and transmission costs by dynamically adjusting the renewable energy generation, load demand and transmission power in each region; The renewable energy generation, load demand and transmission power are adjusted through dynamic threshold monitoring and real-time feedback control functions.

[0007] Furthermore, the information of each region constituting the power system model is determined by: According to the pre-installed sensor equipment in each area, the information of each area constituting the power system model is determined, including the independent renewable energy power generation of each area and the load demand of each area. According to the interconnected transmission lines between the areas, the transmission power between the connected areas is determined. Each area in the power system is identified by a unique number. Each number corresponds to only one area, and the number set representing each area of ​​the power system is obtained, which is recorded as , where i represents the region numbered i, n represents the region numbered n and the power system is composed of n regions. Determine the average power generation cost of each power system region within a period of t.

[0008] Furthermore, an objective function is established with the goal of minimizing the power generation cost of the power system, and a multi-regional interconnected power system model is constructed. The specific method is as follows: The multi-regional interconnected power system model establishes the objective function by minimizing the total power generation cost while satisfying the power balance and transmission constraints of each region. represents the objective function of minimizing the total power generation cost, where i represents the region numbered i, n represents the region numbered n and the power system is composed of n regions, represents the normal power generation of area i after a period of time of h, The power generation cost function represents the conventional power generation of region i. The power generation cost function uses the formula Indicates that The quadratic coefficient of the power generation cost in region i represents the nonlinear part of the power generation cost increasing with the power generation, which is related to the efficiency curve of the generator in the region. The linear coefficient of the power generation cost of region i represents the linear part of the power generation cost increasing with the power generation, which is directly related to the fuel consumption and maintenance cost of the region. The constant term representing the cost of electricity generation in region i represents the fixed cost of the generator in this region, such as the startup cost of the generator, which is independent of the amount of electricity generated.

[0009] Furthermore, to meet the power balance and transmission constraints of each region, the specific method is as follows: The power balance constraint of region i is used as formula Indicates, where i represents the region numbered i, j represents the region numbered j, , n represents the area numbered n and the power system is composed of n areas, represents the normal power generation of area i after a period of time of h, represents the amount of renewable energy generated in region i after a period of h, represents the transmission power between area i and area j. When it is greater than 0, it means that power is transferred from area i to area j. When it is less than 0, it means that power is transferred from area j to area i. When it is equal to 0, it means there is no power transmission between area i and area j. represents the average load demand of area i every h time period; The transmission power constraint between area i and area j is calculated using the formula express; The conventional power generation constraint utilization formula for region i It indicates that, It represents the minimum power generation of area i after h time, It represents the maximum power generation of area i after a period of time h.

[0010] Furthermore, the objective function of optimizing the consumption of new energy is to maximize the consumption of new energy. The specific method is as follows: Using the formula represents the objective function of optimizing the consumption of new energy by maximizing the consumption of new energy, where: Represents the weight coefficient of new energy consumption in region i. The weight coefficient of new energy consumption is used to reflect the priority of new energy consumption in different regions. For example, a higher weight coefficient can be set for regions with rich new energy resources. It represents the renewable energy power generation of region i after a period of time of h; Based on the objective function of new energy consumption optimization, the constraints of new energy consumption are determined, and the formula represents the renewable energy generation capacity constraint in region i, where represents the maximum power generation of renewable energy in region i; Using the formula represents the new energy consumption rate constraint of region i, where Represents the minimum consumption rate of new energy in region i.

[0011] Furthermore, the conventional power generation of each region and the transmission power between regions are adjusted based on the Lagrangian function optimization algorithm. The specific method is as follows: Using the formula represents the Lagrangian function, where L represents the Lagrangian function, represents the weight coefficient of new energy consumption in region i, It represents the Lagrangian operator of the Lagrangian function constructed for region i. By taking partial derivatives of the unknown quantities of new energy consumption, conventional power generation and transmission power in the Lagrangian function, the functional relationship for the optimal solution of new energy consumption, conventional power generation and transmission power is obtained. Combined with the corresponding constraints, the optimized values ​​of new energy consumption, conventional power generation and transmission power in each region are obtained.

[0012] Furthermore, the renewable energy generation, load demand and transmission power are adjusted through dynamic threshold monitoring and real-time feedback control functions. The specific method is as follows: By real-time monitoring of the renewable energy power generation, load demand and transmission power of each region, the renewable energy power generation threshold, load demand threshold and transmission power threshold are preset for each region in different power generation time periods, and the time periods are divided. The duration of each time period is h, and the average values ​​of renewable energy power generation, load demand and transmission power of region i in each time period are determined. The calculated average values ​​are compared with the preset threshold values. If any average value of renewable energy power generation, load demand or transmission power of a region in a certain time period reaches or exceeds its corresponding threshold value, the dynamic adjustment mechanism is triggered. When the dynamic adjustment mechanism is triggered, the system adjusts the renewable energy power generation, load demand and transmission power of the region in the next time period according to the real-time feedback control function.

[0013] Furthermore, the real-time feedback control function has a specific formula as follows: ;

[0014] Where i represents the area numbered i, j represents the area numbered j, x represents the xth time period, and x+1 represents the next time period after the xth time period. represents the conventional power generation in the xth time period of region i, represents the renewable energy power generation in region i in the xth time period, represents the transmission power between area i and area j in the xth time period, is the new energy volatility weight coefficient of region i, Represents the transmission change weight coefficient of region i.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. The present invention establishes an objective function with the goal of minimizing the power generation cost of the power system, and can comprehensively consider the power generation cost of each region, the power generation of new energy, the load demand and the transmission power between regions, so as to formulate the optimal power generation and transmission strategy. By constructing a multi-regional interconnected power system model, it is helpful to realize the cross-regional scheduling and optimal configuration of power resources, and improve the operating efficiency and stability of the entire power system; 2. The present invention helps to maximize the consumption of new energy by adjusting the conventional power generation of each region and the transmission power between regions, thereby improving the utilization rate of new energy. The dynamic adjustment mechanism of the present invention can adjust the load demand and transmission power of new energy power generation according to real-time conditions, thereby avoiding waste and overuse of resources, helping to improve the utilization efficiency of power resources and reduce power generation and transmission costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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 of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A step diagram of a new energy consumption and power supply method based on multi-region interconnection is shown; Figure 2 A method step diagram for dynamic adjustment based on a real-time feedback control function is shown. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Embodiment 1: Figure 1 , Figure 2 The new energy consumption and power supply method based on multi-region interconnection shown specifically includes the following steps: Step 1: Establish an objective function with the goal of minimizing the power generation cost of the power system and construct a multi-regional interconnected power system model.

[0020] According to the sensor equipment pre-installed in each area, such as power sensors, current sensors and charge sensors, the information of each area constituting the power system model is determined, including the independent renewable energy generation of each area and the load demand of each area. According to the interconnected transmission lines between the areas, the transmission power between the connected areas is determined. Each area in the power system is identified by a unique number. Each number corresponds to only one area, and a set of numbers representing each area of ​​the power system is obtained, which is recorded as , where i represents the region numbered i, n represents the region numbered n and the power system is composed of n regions. The average power generation cost of each power system region within a time period of t is determined. The multi-region interconnected power system model establishes an objective function to minimize the total power generation cost while satisfying the power balance and transmission constraints of each region. The objective function is as follows: ; Among them, i represents the area numbered i, n represents the area numbered n and the power system is composed of n areas. represents the normal power generation of area i after a period of time of h, The power generation cost function represents the conventional power generation of region i. The power generation cost function uses the formula Indicates that The quadratic coefficient of the power generation cost in region i represents the nonlinear part of the power generation cost increasing with the power generation, which is related to the efficiency curve of the generator in the region. The linear coefficient of the power generation cost of region i represents the linear part of the power generation cost increasing with the power generation, which is directly related to the fuel consumption and maintenance cost of the region. The constant term representing the cost of electricity generation in region i represents the fixed cost of the generator in this region, such as the startup cost of the generator, which is independent of the amount of electricity generated.

[0021] The power balance constraints of region i are as follows: ; Among them, i represents the area numbered i, j represents the area numbered j, , n represents the area numbered n and the power system is composed of n areas, represents the normal power generation of area i after a period of time of h, represents the amount of renewable energy generated in region i after a period of h, represents the transmission power between area i and area j. When it is greater than 0, it means that power is transferred from area i to area j. When it is less than 0, it means that power is transferred from area j to area i. When it is equal to 0, it means there is no power transmission between area i and area j. It represents the average load demand of area i every time period h.

[0022] The transmission power constraint between area i and area j is as follows: ; The conventional power generation constraints of region i are as follows: ; in, It represents the minimum power generation of area i after h time, It represents the maximum power generation of area i after a period of time h.

[0023] Step 2: Adjust the conventional power generation of each region and the transmission power between regions to maximize the utilization rate of new energy and optimize the consumption of new energy.

[0024] The objective function of new energy consumption optimization is to maximize the consumption of new energy, as shown below: ; in, Represents the weight coefficient of new energy consumption in region i. The weight coefficient of new energy consumption is used to reflect the priority of new energy consumption in different regions. For example, a higher weight coefficient can be set for regions with rich new energy resources. It represents the renewable energy power generation in area i after a period of time of h.

[0025] Based on the objective function of new energy consumption optimization, determine the constraints of new energy consumption, including new energy power generation constraints and new energy consumption rate constraints; The specific constraints on renewable energy generation in region i are as follows: ; in represents the maximum renewable energy generation capacity of region i, which is determined by the renewable energy resources in the region; The specific constraints on the new energy consumption rate of region i are as follows: ; in It represents the minimum consumption rate of new energy in region i, which is used to ensure the utilization rate of new energy in the region.

[0026] Based on the objective function of minimizing the power generation cost of the power system and optimizing the consumption of new energy, combined with the corresponding constraints, a Lagrangian function is constructed as an optimization algorithm for the consumption of new energy. The specific Lagrangian function is as follows: ; Where L represents the Lagrangian function, represents the weight coefficient of new energy consumption in region i, It represents the Lagrangian operator of the Lagrangian function constructed for region i. By taking partial derivatives of the unknown quantities of new energy consumption, conventional power generation and transmission power in the Lagrangian function, we get the functional relationship of the optimal solution for new energy consumption, conventional power generation and transmission power. Combined with the corresponding constraints, we get the optimized values ​​of new energy consumption, conventional power generation and transmission power in each region to achieve efficient consumption of new energy.

[0027] Step 3: Optimize power generation and transmission costs by dynamically adjusting each region’s renewable energy generation, load demand, and transmission power.

[0028] By real-time monitoring of the renewable energy generation, load demand and transmission power of each region, the renewable energy generation threshold, load demand threshold and transmission power threshold are preset for each region in different generation time periods, and the time periods are divided. The duration of each time period is h, and the average value of renewable energy generation, load demand and transmission power of region i in each time period is determined. The calculated average value is compared with the preset threshold value. If any average value of renewable energy generation, load demand or transmission power of a region in a certain time period reaches or exceeds its corresponding threshold value, the dynamic adjustment mechanism is triggered. When the dynamic adjustment mechanism is triggered, the system adjusts the renewable energy generation, load demand and transmission power of the region in the next time period according to the real-time feedback control function. The specific formula of the real-time feedback control function is as follows: ; Where i represents the area numbered i, j represents the area numbered j, x represents the xth time period, and x+1 represents the next time period after the xth time period. represents the conventional power generation in the xth time period of region i, represents the renewable energy power generation in region i in the xth time period, represents the transmission power between area i and area j in the xth time period, is the new energy volatility weight coefficient of region i, Represents the transmission change weight coefficient of region i.

[0029] According to the adjustment amount calculated by the real-time feedback control function, the system dynamically adjusts the conventional power generation in each region to ensure the frequency and voltage stability of the power system, while maximizing the absorption of new energy and optimizing the power generation cost and transmission cost. The system regularly evaluates the economic benefits of the dynamic adjustment strategy, including the reduction of power generation cost and transmission cost, and the improvement of new energy absorption rate. Based on the benefit evaluation results, the system continuously optimizes the dynamic adjustment strategy, including adjusting the threshold setting, optimizing the parameters of the real-time feedback control function, etc., to achieve more efficient, stable and economical power system operation.

[0030] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0031] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A new energy consumption and power supply method based on multi-regional interconnection, characterized in that: include: Step 1: Establish an objective function with the goal of minimizing the power generation cost of the power system and construct a multi-regional interconnected power system model; Determine the regional information constituting the power system model, wherein the model includes an objective function determined by the regional information, a power balance constraint, a transmission power constraint, and a conventional power generation constraint; Step 2: Adjust the conventional power generation of each region and the transmission power between regions to maximize the utilization rate of new energy and optimize the consumption of new energy; Taking maximizing the consumption of new energy as the objective function of optimizing the consumption of new energy, the conventional power generation in each region and the transmission power between regions are adjusted based on the Lagrangian function optimization algorithm; Step 3: Optimize power generation and transmission costs by dynamically adjusting the renewable energy generation, load demand and transmission power in each region; The renewable energy generation, load demand and transmission power are adjusted through dynamic threshold monitoring and real-time feedback control functions.

2. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 1 is characterized in that: Determine the regional information of each area that constitutes the power system model. The specific method is: According to the pre-installed sensor equipment in each area, the information of each area constituting the power system model is determined, including the independent renewable energy power generation of each area and the load demand of each area. According to the interconnected transmission lines between the areas, the transmission power between the connected areas is determined. Each area in the power system is identified by a unique number. Each number corresponds to only one area, and the number set representing each area of ​​the power system is obtained, which is recorded as , where i represents the region numbered i, n represents the region numbered n and the power system is composed of n regions. Determine the average power generation cost of each power system region within a period of t.

3. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 1 is characterized in that: The objective function is established with the goal of minimizing the power generation cost of the power system, and a multi-regional interconnected power system model is constructed. The specific method is as follows: The multi-regional interconnected power system model establishes the objective function by minimizing the total power generation cost while satisfying the power balance and transmission constraints of each region. represents the objective function of minimizing the total power generation cost, where i represents the region numbered i, n represents the region numbered n and the power system is composed of n regions, represents the normal power generation of area i after a period of time h, The power generation cost function represents the conventional power generation of region i. The power generation cost function uses the formula Indicates that The quadratic coefficient of the power generation cost in region i represents the nonlinear part of the power generation cost increasing with the power generation, which is related to the efficiency curve of the generator in the region. The linear coefficient of the power generation cost of region i represents the linear part of the power generation cost increasing with the power generation, which is directly related to the fuel consumption and maintenance cost of the region. The constant term representing the cost of electricity generation in region i represents the fixed cost of the generator in this region and is independent of the amount of electricity generated.

4. The method for absorbing and supplying new energy based on multi-regional interconnection according to claim 3 is characterized in that: The power balance and transmission constraints of each region are met by: The power balance constraint of region i is used as formula Indicates, where i represents the region numbered i, j represents the region numbered j, , n represents the area numbered n and the power system is composed of n areas, represents the normal power generation of area i after a period of time of h, represents the amount of renewable energy generated in region i after a period of h, represents the transmission power between area i and area j. When it is greater than 0, it means that power is transferred from area i to area j. When it is less than 0, it means that power is transferred from area j to area i. When it is equal to 0, it means there is no power transmission between area i and area j. represents the average load demand of area i every h time period; The transmission power constraint between area i and area j is calculated using the formula express; The conventional power generation constraint utilization formula for region i It indicates that, It represents the minimum power generation of area i after h time, It represents the maximum power generation of area i after a period of time h.

5. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 1 is characterized in that: The objective function of optimizing the consumption of new energy is to maximize the consumption of new energy. The specific method is as follows: Using the formula represents the objective function of optimizing the consumption of new energy by maximizing the consumption of new energy, where: Represents the weight coefficient of new energy consumption in region i. The weight coefficient of new energy consumption is used to reflect the priority of new energy consumption in different regions. It represents the renewable energy power generation of region i after a period of time of h; Based on the objective function of new energy consumption optimization, the constraints of new energy consumption are determined, and the formula represents the renewable energy generation capacity constraint in region i, where represents the maximum power generation of renewable energy in region i; Using the formula represents the new energy consumption rate constraint of region i, where Represents the minimum consumption rate of new energy in region i.

6. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 1 is characterized in that: The conventional power generation in each region and the transmission power between regions are adjusted based on the Lagrangian function optimization algorithm. The specific method is as follows: Using the formula represents the Lagrangian function, where L represents the Lagrangian function, represents the weight coefficient of new energy consumption in region i, It represents the Lagrangian operator of the Lagrangian function constructed for region i. By taking partial derivatives of the unknown quantities of new energy consumption, conventional power generation and transmission power in the Lagrangian function, the functional relationship for the optimal solution of new energy consumption, conventional power generation and transmission power is obtained. Combined with the corresponding constraints, the optimized values ​​of new energy consumption, conventional power generation and transmission power in each region are obtained.

7. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 1 is characterized in that: The renewable energy generation, load demand and transmission power are adjusted through dynamic threshold monitoring and real-time feedback control functions. The specific method is as follows: By real-time monitoring of the renewable energy power generation, load demand and transmission power of each region, the renewable energy power generation threshold, load demand threshold and transmission power threshold are preset for each region in different power generation time periods, and the time periods are divided. The duration of each time period is h, and the average values ​​of renewable energy power generation, load demand and transmission power of region i in each time period are determined. The calculated average values ​​are compared with the preset threshold values. If any average value of renewable energy power generation, load demand or transmission power of a region in a certain time period reaches or exceeds its corresponding threshold value, the dynamic adjustment mechanism is triggered. When the dynamic adjustment mechanism is triggered, the system adjusts the renewable energy power generation, load demand and transmission power of the region in the next time period according to the real-time feedback control function.

8. The method for absorbing and supplying new energy based on multi-region interconnection according to claim 7 is characterized in that: The specific formula of the real-time feedback control function is as follows: ； Where i represents the area numbered i, j represents the area numbered j, x represents the xth time period, and x+1 represents the next time period after the xth time period. represents the normal power generation of area i after a period of time of h, represents the amount of renewable energy generated in region i after a period of h, represents the transmission power between area i and area j, is the new energy volatility weight coefficient of region i, Represents the transmission change weight coefficient of region i.

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