Method for evaluating new energy consumption capability of Saggou project

Abstract

The invention relates to the technical field of new energy consumption, and discloses a method for evaluating the new energy consumption capability of a Sagomei project, and the method comprises the steps: S1, carrying out the system evaluation of the renewable energy of a Sagomei project region, the technical characteristics of new energy power generation equipment, and the power grid bearing capability and potential bottleneck of the region; s2, artificial intelligence and big data technologies are introduced, and accurate scheduling and control coordinated power generation are carried out on new energy power generation equipment; s3, simulating the operation condition of the power grid after new energy grid connection by using simulation software; s4, formulating corresponding scheduling strategies and optimization measures according to problems and bottlenecks found in simulation results; s5, evaluating the influence of new energy consumption on the safe operation of the power grid; and S6, comprehensively considering factors in the aspects of technical cost, operation cost and power grid operation benefit of new energy consumption, rapidly adjusting an operation strategy and control parameters, and improving adaptability and stability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy consumption, and in particular to a method for evaluating the new energy consumption capacity of a Shagohuang project. Background Art

[0002] With the rapid development of the new energy industry, the demand for the evaluation of new energy absorption capacity is gradually increasing. In the Shaxia Desert Project, the evaluation of new energy absorption capacity is one of the keys to the smooth implementation and operation of the project. Through scientific and reasonable evaluation methods, the construction and operation efficiency of new energy projects can be effectively improved, and the optimization of energy structure and improvement of ecological environment can be promoted;

[0003] In order to simplify the evaluation process, traditional evaluation may adopt some theoretical models or assumptions, but these simplified models or assumptions may deviate from the actual situation, resulting in evaluation results that are inconsistent with the actual situation. At the same time, the professional level and technical capabilities of the evaluators may be insufficient to fully understand and apply new energy consumption technologies, resulting in low credibility of the evaluation results, making it difficult to conduct a comprehensive evaluation.

[0004] After searching, the Chinese patent number CN116663968A discloses a method and device for evaluating the value system of energy storage systems that consider the new energy absorption capacity. It promotes the absorption of new energy and improves the reasonable utilization rate of new energy by constructing a new energy absorption model, realizes the quantitative analysis of the economic, technical and environmental value of the power system including energy storage, greatly reduces the wind and solar abandonment rate of the energy storage system, improves the operating cost saving rate, and slightly increases the proportion of new energy power generation and carbon emission reduction rate.

[0005] However, the above-mentioned patents need professional technicians to operate and analyze, which requires high professional level and technical ability of evaluators. In addition, in the evaluation process, too much emphasis may be placed on one factor while ignoring the influence of other factors, resulting in one-sidedness and incompleteness of the evaluation results. Therefore, a method for evaluating the new energy absorption capacity of the Shagohuang project is proposed. Summary of the invention

[0006] The present invention proposes a method for evaluating the new energy absorption capacity of the Shagohuang project in order to solve the problem that traditional methods have high requirements on the professional level and technical ability of evaluators, and may overemphasize certain factors during the evaluation process, resulting in one-sidedness and incompleteness of the evaluation results.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] S1: Conduct a systematic assessment of the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area and the grid carrying capacity and potential bottlenecks in the area;

[0009] S2: Introducing artificial intelligence and big data technologies to accurately dispatch and control new energy power generation equipment to coordinate power generation;

[0010] S3: Use simulation software to simulate the operation of the power grid after the new energy is connected to the grid;

[0011] S4: Develop corresponding scheduling strategies and optimization measures based on the problems and bottlenecks found in the simulation results;

[0012] S5: Assess the impact of new energy consumption on the safe operation of the power grid;

[0013] S6: Comprehensively consider the technical cost, operating cost and grid operation efficiency factors of new energy consumption.

[0014] The above technical solution further includes:

[0015] S1: Conduct a systematic assessment of the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area, as well as the power grid carrying capacity and potential bottlenecks in the area. Obtain new energy resource data in the Shagohuang project area through existing measurement equipment, satellite images and meteorological data. Use the collected data to establish a resource model and conduct long-term and short-term resource forecasts. At the same time, conduct an assessment of electricity demand based on regional load demand, new energy resource conditions and user demand factors.

[0016] S2: Introducing artificial intelligence and big data technologies, accurately dispatching and controlling new energy power generation equipment to coordinate power generation, evaluating the new energy consumption capacity of the Shagohuang project, and establishing an optimization problem. By maximizing the objective function of system reliability, while satisfying the constraints of power grid transmission line capacity and node voltage stability, the general form of this optimization problem is expressed as:

[0017] max x f(x)

[0018] stg i (x)≤0,i=1,2,...,m

[0019] h j (x)=0,j=1,2,...,n

[0020] Where x is the variable vector to be optimized, f(x) is the objective function, and g i (x) and h j (x) are the inequality constraint and equality constraint functions respectively. The gradient descent method is used to optimize the problem. Taking the gradient descent method as an example, its iterative update formula is:

[0021] x k+1 =x k -α▽f(xk )

[0022] Where α is the learning rate, ▽f(x k ) is the objective function at the current point x k The gradient at , uses the gradient descent method to continuously update the variable x until the convergence condition is met or the maximum number of iterations is reached.

[0023] The S3: Use simulation software to simulate the operation of the power grid after the new energy is connected to the grid, dynamically respond under external disturbances, evaluate the stability of the system, simulate the dispatching and control algorithms in the smart grid system through the transient response of the protection system and control strategy in a short period of time, and perform parameter tuning, through the communication and coordination between the nodes in the control system, and the emergency response under emergencies, to evaluate the effectiveness of the emergency response plan, guide the construction of the power grid and the long-term planning, development and operation.

[0024] S4: formulate corresponding dispatching strategies and optimization measures for the problems and bottlenecks found in the simulation results, use the optimization algorithm to dispatch the power system, and consider the supply and demand balance, transmission line capacity and voltage stability constraints in the dispatching process, monitor the operation status of the power system in real time, detect abnormal situations in time and make adjustments, and evaluate the performance of the optimized dispatching scheme. Adjust the optimization model and algorithm according to the evaluation results, and continuously improve the dispatching strategies and methods.

[0025] S5: Assess the impact of new energy consumption on the safe operation of the power grid, identify security risks and potential threats in the system, analyze the probability and impact of various risks, analyze and evaluate the vulnerabilities in the system, formulate emergency response plans and countermeasures, and provide security training for system operators and managers to deal with emergencies when the system is attacked or suffers from emergencies.

[0026] S6: Comprehensively consider the technical cost, operation cost and grid operation efficiency of new energy consumption, optimize the generator output and transmission line power distribution to maximize the system benefits or meet the constraints, use the optimal power flow algorithm based on the Newton-Raphson method for analysis, establish the power flow model and power balance equation of the power system, and use the Newton-Raphson method for iterative solution. The general form of the power flow model is as follows:

[0027] P=B·V·V T

[0028] Q=B·V·V T

[0029] Where P and Q are the node injected active power and reactive power vectors, V is the node voltage complex vector, and B is the node admittance matrix.

[0030] The power flow model is constructed by setting up an optimization problem:

[0031]

[0032] stP(P g ,P l )≤P max

[0033] Q(P g ,P l )≤Q max

[0034] Vmin≤V≤Vmax

[0035] Among them, P g and P l are the generator output and load power vector, C i (·) is the power generation cost function, Pmax and Qmax are the upper limits of the injected power, Vmin and Vmax are the lower and upper limits of the node voltage, respectively. By solving this optimization problem, the optimal generator output distribution and transmission line power distribution are obtained, and the grid’s absorption capacity is evaluated.

[0036] The present invention has the following beneficial effects:

[0037] 1. In the present invention, simulation can be based on real data and scenarios, and has high flexibility and adjustability, and parameters can be adjusted and models optimized according to different scenarios and needs, so as to better meet the actual needs of evaluation and more accurately simulate the new energy consumption process.

[0038] 2. In the present invention, the operating parameters of the power system are adjusted in time through intelligent scheduling and control means, and the operating strategy and control parameters are quickly adjusted according to the actual needs of the power system and changes in the external environment to improve the adaptability and stability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is an overall framework diagram of the new energy consumption capacity evaluation method for the Shagohuang project proposed in the present invention. DETAILED DESCRIPTION

[0040] Embodiment 1

[0041] 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.

[0042] like Figure 1 As shown, the present invention proposes a method for evaluating the new energy consumption capacity of the Shagohuang project, including: S1: systematically evaluating the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area and the power grid carrying capacity and potential bottlenecks in the area; S2: introducing artificial intelligence and big data technology to accurately dispatch and control the coordinated power generation of new energy power generation equipment; S3: using simulation software to simulate the operation of the power grid after the new energy is connected to the grid; S4: formulating corresponding dispatching strategies and optimization measures for the problems and bottlenecks found in the simulation results; S5: evaluating the impact of new energy consumption on the safe operation of the power grid; S6: comprehensively considering the technical cost, operation cost and power grid operation efficiency of new energy consumption;

[0043] S1: Conduct a systematic assessment of the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area, as well as the power grid carrying capacity and potential bottlenecks in the area. Obtain new energy resource data in the Shagohuang project area through existing measurement equipment, satellite images and meteorological data. Use the collected data to establish a resource model and conduct long-term and short-term resource forecasts. At the same time, conduct an assessment of power demand based on regional load demand, new energy resource conditions and user demand factors;

[0044] S2: Introducing artificial intelligence and big data technologies, accurately dispatching and controlling the coordinated power generation of new energy power generation equipment, evaluating the new energy consumption capacity of the Shagohuang project, and establishing an optimization problem. By maximizing the objective function of system reliability, while satisfying the constraints of the power grid's transmission line capacity and node voltage stability, the general form of this optimization problem is expressed as:

[0045] max x f(x)

[0046] stg i (x)≤0,i=1,2,...,m

[0047] h j (x)=0,j=1,2,...,n

[0048] Where x is the variable vector to be optimized, f(x) is the objective function, and g i (x) and h j (x) are the inequality constraint and equality constraint functions respectively. The gradient descent method is used to optimize the problem. Taking the gradient descent method as an example, its iterative update formula is:

[0049] x k+1 =x k -α▽f(x k )

[0050] Where α is the learning rate, ▽f(x k ) is the objective function at the current point x k The gradient at , using the gradient descent method to continuously update the variable x until the convergence condition is met or the maximum number of iterations is reached;

[0051] S3: Use simulation software to simulate the operation of the power grid after the connection of new energy to the grid, dynamically respond under external disturbances, evaluate the stability of the system, simulate the dispatching and control algorithms in the smart grid system through the transient response of the protection system and control strategy in a short period of time, and perform parameter tuning. Through the communication and coordination between the nodes in the control system, the emergency response under emergencies is evaluated to evaluate the effectiveness of the emergency response plan and guide the construction of the power grid and the long-term planning, development and operation.

[0052] In this embodiment, by systematically evaluating the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area, the power grid carrying capacity and potential bottlenecks in the area, as well as the distribution, intensity and seasonal changes of resources, the capacity, load characteristics and transmission capacity of the power grid, including the power curve of wind turbines and the output characteristics of photovoltaic battery groups, and by introducing artificial intelligence and big data technologies, the new energy power generation equipment is precisely dispatched and controlled to coordinate power generation;

[0053] Build a smart grid system to achieve accurate dispatch and control of new energy power generation equipment, use simulation software to simulate the operation of the grid after the new energy is connected to the grid, conduct comprehensive and in-depth analysis and testing of the grid system in a virtual environment, and provide reference and support for practical applications.

[0054] Embodiment 2

[0055] like Figure 1 As shown, in the embodiment of the present invention, S4: formulate corresponding dispatching strategies and optimization measures for the problems and bottlenecks found in the simulation results, use the optimization algorithm to dispatch the power system, and consider the supply and demand balance, transmission line capacity and voltage stability constraints in the dispatching process, and monitor the operation status of the power system in real time, detect abnormal conditions in time and make adjustments, and evaluate the performance of the optimized dispatching scheme, adjust the optimization model and algorithm according to the evaluation results, and continuously improve the dispatching strategy and method;

[0056] S5: Assess the impact of new energy consumption on the safe operation of the power grid, identify security risks and potential threats in the system, analyze the probability and impact of various risks, analyze and evaluate the vulnerabilities in the system, formulate emergency response plans and countermeasures, and provide security training for system operators and managers to deal with emergency situations when the system is attacked or suffers from emergencies;

[0057] S6: Comprehensively consider the technical cost, operation cost and grid operation efficiency of renewable energy consumption, optimize the generator output and transmission line power distribution to maximize the system benefits or meet the constraints, use the optimal power flow algorithm based on the Newton-Raphson method for analysis, establish the power flow model and power balance equation of the power system, and use the Newton-Raphson method for iterative solution. The general form of the power flow model is as follows:

[0058] P=B·V·V T

[0059] Q=B·V·V T

[0060] Where P and Q are the node injected active power and reactive power vectors, V is the node voltage complex vector, and B is the node admittance matrix;

[0061] The power flow model is constructed by formulating an optimization problem:

[0062]

[0063] stP(P g ,P l )≤P max

[0064] Q(P g ,P l )≤Q max

[0065] Vmin≤V≤Vmax

[0066] Among them, P g and P l are the generator output and load power vector, C i (·) is the power generation cost function, Pmax and Qmax are the upper limits of the injected power, Vmin and Vmax are the lower and upper limits of the node voltage, respectively. By solving this optimization problem, the optimal generator output distribution and transmission line power distribution are obtained, and the grid’s absorption capacity is evaluated.

[0067] In this embodiment, by formulating corresponding dispatching strategies and optimization measures for the problems and bottlenecks found in the simulation results, efficient operation of the power system and rational use of resources are achieved, large-scale access and consumption of renewable energy are promoted, and the impact of new energy consumption on the safe operation of the power grid is evaluated. The security of the smart grid system is comprehensively evaluated, and effective measures are taken to ensure the safe operation of the system and the confidentiality, integrity and availability of data. At the same time, the technical cost, operating cost and power grid operation efficiency of new energy consumption are comprehensively considered, and the economic evaluation of new energy consumption capacity is carried out to determine the optimal consumption plan.

[0068] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for evaluating the new energy consumption capacity of the Shagohuang project. It is characterized in that include: S1: Conduct a systematic assessment of the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area and the grid carrying capacity and potential bottlenecks in the area; S2: Introducing artificial intelligence and big data technologies to accurately dispatch and control new energy power generation equipment to coordinate power generation; S3: Use simulation software to simulate the operation of the power grid after the new energy is connected to the grid; S4: Develop corresponding scheduling strategies and optimization measures based on the problems and bottlenecks found in the simulation results; S5: Assess the impact of new energy consumption on the safe operation of the power grid; S6: Comprehensively consider the technical cost, operating cost and grid operation efficiency factors of new energy consumption.

2. According to the method for evaluating the new energy consumption capacity of the Shagohuang project in claim 1, It is characterized in that S1: Conduct a systematic assessment of the technical characteristics of renewable energy and new energy power generation equipment in the Shagohuang project area, as well as the power grid carrying capacity and potential bottlenecks in the area. Obtain new energy resource data in the Shagohuang project area through existing measurement equipment, satellite images and meteorological data. Use the collected data to establish a resource model and conduct long-term and short-term resource forecasts. At the same time, conduct an assessment of electricity demand based on regional load demand, new energy resource conditions and user demand factors.

3. According to claim 1, a method for evaluating the new energy consumption capacity of the Shagohuang project, It is characterized in that S2: Introducing artificial intelligence and big data technologies, accurately dispatching and controlling new energy power generation equipment to coordinate power generation, evaluating the new energy consumption capacity of the Shagohuang project, and establishing an optimization problem. By maximizing the objective function of system reliability, while satisfying the constraints of power grid transmission line capacity and node voltage stability, the general form of this optimization problem is expressed as: max x f(x) s.t.g i (x)≤0,i=1,2,...,m h j (x)=0,j=1,2,...,n Where x is the variable vector to be optimized, f(x) is the objective function, and g i (x) and h j (x) are the inequality constraint and equality constraint functions respectively. The gradient descent method is used to optimize the problem. Taking the gradient descent method as an example, its iterative update formula is: x k+1 =x k -α▽f(x k ) Where α is the learning rate, ▽f(x k ) is the objective function at the current point x k The gradient at , uses the gradient descent method to continuously update the variable x until the convergence condition is met or the maximum number of iterations is reached.

4. According to claim 1, a method for evaluating the new energy consumption capacity of the Shagohuang project, It is characterized in that The S3: Use simulation software to simulate the operation of the power grid after the new energy is connected to the grid, dynamically respond under external disturbances, evaluate the stability of the system, simulate the dispatching and control algorithms in the smart grid system through the transient response of the protection system and control strategy in a short period of time, and perform parameter tuning, through the communication and coordination between the nodes in the control system, and the emergency response under emergencies, to evaluate the effectiveness of the emergency response plan, guide the construction of the power grid and the long-term planning, development and operation.

5. According to claim 1, a method for evaluating the new energy consumption capacity of the Shagohuang project, It is characterized in that S4: formulate corresponding dispatching strategies and optimization measures for the problems and bottlenecks found in the simulation results, use the optimization algorithm to dispatch the power system, and consider the supply and demand balance, transmission line capacity and voltage stability constraints in the dispatching process, monitor the operation status of the power system in real time, detect abnormal situations in time and make adjustments, and evaluate the performance of the optimized dispatching scheme. Adjust the optimization model and algorithm according to the evaluation results, and continuously improve the dispatching strategies and methods.

6. According to claim 1, a method for evaluating the new energy consumption capacity of the Shagohuang project, It is characterized in that S5: Assess the impact of new energy consumption on the safe operation of the power grid, identify security risks and potential threats in the system, analyze the probability and impact of various risks, analyze and evaluate the vulnerabilities in the system, formulate emergency response plans and countermeasures, and provide security training for system operators and managers to deal with emergencies when the system is attacked or suffers from emergencies.

7. A method for evaluating the new energy consumption capacity of the Shagohuang project according to claim 6, It is characterized in that S6: Comprehensively consider the technical cost, operation cost and grid operation efficiency of new energy consumption, optimize the generator output and transmission line power distribution to maximize the system benefits or meet the constraints, use the optimal power flow algorithm based on the Newton-Raphson method for analysis, establish the power flow model and power balance equation of the power system, and use the Newton-Raphson method for iterative solution. The general form of the power flow model is as follows: P=B·V·V T Q=B·V·V T Where P and Q are the node injected active power and reactive power vectors, V is the node voltage complex vector, and B is the node admittance matrix.

8. According to claim 7, a method for evaluating the new energy consumption capacity of the Shagohuang project, It is characterized in that The power flow model is constructed by setting up an optimization problem: s.t.P(P g ,P l )≤P max Q(P g ,P l )≤Q max Vmin≤V≤Vmax Among them, P g and P l are the generator output and load power vector, C i (·) is the power generation cost function, Pmax and Qmax are the upper limits of the injected power, Vmin and Vmax are the lower and upper limits of the node voltage, respectively. By solving this optimization problem, the optimal generator output distribution and transmission line power distribution are obtained, and the grid’s absorption capacity is evaluated.

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