Distributed power grid operation optimization method considering price guiding mechanism

Abstract

The invention discloses a distributed power grid operation optimization method considering a price guiding mechanism, and the method comprises the following steps: S1, building a price guiding mechanism model: collecting the real-time data of various distributed resources (such as distributed energy, an energy storage device, a controllable load and the like) in a distributed power grid, and obtaining the electricity price information of an external power grid, comprising real-time electricity prices, time-of-use electricity prices and the like, a price guiding model reflecting market price signals is established based on the collected data, and meanwhile the model can accurately reflect changes of market supply and demand relations and response characteristics of distributed resources to the price signals; and S2, optimizing distributed resource scheduling: adjusting a power generation plan of distributed energy according to a price signal provided by the price guiding model. According to the distributed power grid operation optimization method considering the price guidance mechanism, the safety and stability of a power system can be improved, the operation cost of the power system is reduced, and meanwhile, the development of the new energy industry is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid optimization, and in particular to a distributed power grid operation optimization method taking into account a price guidance mechanism. Background Art

[0002] In 2022, my country's new installed capacity of wind power and photovoltaic power generation reached 125 million kilowatts, setting a new historical high. Among them, distributed photovoltaic power generation added 51.11 million kilowatts, a year-on-year increase of 74.6%. Distributed new energy in the distribution network ushered in explosive growth. As the proportion of renewable energy power increases, the safe and reliable operation of the distribution network faces new challenges.

[0003] The access of distributed generation (DG) has expanded the operation mode of the distribution network, and has also greatly increased the complexity of the distribution network. The access of DG has changed the network structure of the traditional distribution network, changed the power flow and fault current of the distribution network, and made the fault characteristics more complex. With the access of a large number of DGs, the requirement of DGs to be disconnected from the grid immediately when a fault occurs in the grid in the early grid connection regulations is no longer applicable, because the sudden disconnection of large-scale DGs may bring great instability to the distribution network and even cause the grid to paralyze. Therefore, in order to enhance the stability of the system when DGs are connected, when a fault occurs in the distribution network, DGs cannot be disconnected from the grid immediately, but also need to provide reactive current to the grid to support the grid voltage. The output of the inverter-type DG is affected by its control strategy and has strong nonlinearity, making the traditional fault analysis method and the protection method based on the traditional fault characteristics no longer applicable. The traditional protection device has a series of problems such as false operation, refusal to operate, and fault clearing delay, which will induce a long-term power outage of the system in severe cases. In addition, when the main power grid is out of power, the high-penetration DG distribution network can operate in an isolated microgrid mode. Its fault characteristics are completely determined by the circuit topology and control strategy of the DG, further exacerbating the difficulty of its fault protection.

[0004] Therefore, we propose a distributed power grid operation optimization method taking into account the price guidance mechanism to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a distributed power grid operation optimization method taking into account a price guidance mechanism, so as to solve the problem proposed in the above background technology that with the large-scale access of DG, the requirement of DG being immediately disconnected from the grid when a grid failure occurs in the early grid-connected regulations is no longer applicable, because the sudden disconnection of large-scale DG may bring great instability to the distribution network and even cause the grid to paralyze.

[0006] To achieve the above object, the present invention provides the following technical solution: a distributed power grid operation optimization method taking into account a price guidance mechanism, comprising the following steps: S1. Construct a price guidance mechanism model: collect real-time data of various distributed resources (such as distributed energy, energy storage devices, controllable loads, etc.) in the distributed power grid, and obtain electricity price information of the external power grid, including real-time electricity price, time-of-use electricity price, etc., and establish a price guidance model that reflects market price signals based on the collected data. At the same time, the model should be able to accurately reflect the changes in market supply and demand, as well as the response characteristics of distributed resources to price signals; S2. Optimize the scheduling of distributed resources: According to the price signals provided by the price guidance model, adjust the power generation plan of distributed energy, and increase the power generation of distributed energy during the period of high electricity prices; reduce the power generation or store energy during the period of low electricity prices, and optimize the charging and discharging strategy of energy storage equipment according to price signals, and charge during the period of low electricity prices to store energy; discharge during the period of high electricity prices to release energy and obtain economic benefits, and guide the controllable load to adjust its electricity consumption behavior through price signals, and reduce or transfer electricity consumption during the period of high electricity prices; increase electricity consumption during the period of low electricity prices; S3. Coordinated interactive response of distributed resources: Based on multi-agent theory or similar methods, a coordinated operation strategy among distributed resources is constructed. At the same time, distributed resource agents interact and respond to other resource agents according to their own needs and price signals, and set priorities for each distributed resource agent according to the size of the interactive benefits. At the same time, in each operating time period, the needs of each resource agent are responded to in order of priority; S4. Establish a real-time monitoring system to monitor the operating status and interaction of various resources in the distributed power grid, and promptly discover and solve possible problems. By comparing the power grid operation data before and after optimization, evaluate the effect of the price guidance mechanism on the optimization of distributed power grid operation, and adjust and optimize the price guidance model and dispatch strategy based on the evaluation results. S5. Feedback and adjustment: Adjust and optimize the price guidance model and dispatch strategy based on user feedback and evaluation results, and continuously improve the operation optimization methods of distributed power grids.

[0007] Preferably, in S1, a mathematical model of the distribution network is established to analyze the impact of the access of distributed power sources to the distribution network on voltage stability, and the load-side dispatchable resources are introduced into the distribution network voltage coordination control by analyzing the comprehensive demand response characteristics of the load side. Secondly, the model is solved by the CPLEX solver in Matlab to obtain the output of each coordinated control device, energy storage and time-shiftable load participating in the distribution network voltage coordination control, so as to verify the feasibility of the method. Finally, a distribution network voltage coordination control model with low-carbon characteristics is formed by introducing a step-type carbon trading mechanism, and an objective function is established with the lowest network loss cost, the lowest interruptible load cost and the lowest carbon trading cost. An optimization strategy for the distribution network voltage coordination control method containing distributed power sources is proposed, and simulation verification is carried out in combination with the improved IEEE33 node system.

[0008] Preferably, in S1, by performing power flow calculation on the distribution network containing distributed power, the influence of the access of distributed power sources on the fault section location of the distribution network is analyzed, and a fault section location model of the distribution network containing distributed power sources is established based on a coding method that can reflect the direction of the fault current, a switching function that can dynamically reflect the number of distributed power sources accessed, and a fitness function with fault-tolerant performance. The model is solved by introducing an artificial intelligence algorithm (genetic algorithm, particle swarm algorithm, ant colony algorithm, etc.) to form a fast and accurate section method for single-point faults, multi-point faults, and faults with information distortion.

[0009] Preferably, in S1, an island division model based on load levels is established to optimally divide the range of distributed power sources with independent power supply capabilities, an artificial intelligence algorithm is introduced to recover and reconstruct the network outside the island after a fault occurs, and an efficient and reliable fault recovery and reconstruction method is formed by reducing the scope of the solution space and increasing the search rate.

[0010] Preferably, in S2, key variables affecting the operation of the power grid are selected as optimization variables, such as the output of distributed power sources, the charging and discharging strategies of energy storage equipment, the scheduling of loads, etc., and corresponding objective functions are established according to the optimization objectives, such as minimizing operating costs, maximizing energy efficiency, etc., and considering the physical constraints of the power grid (such as line capacity, voltage range, etc.) and operating constraints (such as load demand, output limit of distributed power sources, etc.), corresponding constraints are set.

[0011] Preferably, in S2, a suitable optimization algorithm is selected according to the complexity and constraints of the optimization model, such as a genetic algorithm, a particle swarm algorithm, a simulated annealing algorithm, etc., and parameters of the selected optimization algorithm are configured, such as population size, number of iterations, crossover probability, mutation probability, etc.

[0012] Preferably, in S3, a transient characteristic analysis model of distributed power sources is established, an analytical expression of fault current is obtained, and the fault current characteristics of distributed power sources under various control strategies are compared and analyzed. Then, the fault ride-through control method of distributed power sources is studied, and a fast fault ride-through method is designed by combining the fault characteristics of distributed power sources with the requirements of the distribution network system level.

[0013] Preferably, the photovoltaic, wind turbine and energy storage in S3 are connected to the AC bus via a power electronic converter, wherein the control strategies of the power electronic converter mainly include constant current control, constant power control, constant voltage control and droop control, wherein constant current control and constant power control belong to current type control strategies, constant voltage control and droop control belong to voltage type control strategies, and appropriate converter control strategies are selected according to different scenarios and different operating modes of the distribution network containing DG.

[0014] Preferably, the DG in S3 is connected to the AC bus through an interface converter, and the distribution network containing high-penetration DG can operate in an island mode in addition to grid-connected operation, in which the DG switching control strategy continues to maintain the stable operation of the distribution network.

[0015] Compared with the prior art, the beneficial effects of the present invention are: the distributed power grid operation optimization method taking into account the price guidance mechanism can improve the safety and stability of the power system and reduce the operating cost of the power system, while also promoting the development of the new energy industry. The specific contents are as follows: (1) The price guidance mechanism regulates resource allocation through market mechanisms, enabling distributed power grids to adjust energy production and consumption according to market price signals, thereby reducing operating costs. At the same time, renewable energy generation units in distributed power grids can consume electricity locally, reducing line losses and costs in the transmission and transformation process; Furthermore, the price guidance mechanism encourages distributed power grids to optimize energy production and consumption and improve energy efficiency, and the renewable energy generation units in distributed power grids can make full use of renewable energy, reduce fossil fuel consumption, and reduce energy costs; (2) The price guidance mechanism enables distributed power grids to flexibly respond to changes in market prices and adjust energy production and consumption strategies. At the same time, the renewable energy generation units in the distributed power grid can be started and stopped quickly and are easy to operate, so they can flexibly respond to changes in electricity demand. Furthermore, the distributed power grid is independent and can maintain continuous and stable power supply to important loads when a large power grid fails. At the same time, the renewable energy power generation units in the distributed power grid can be distributed to reduce the impact of a single fault point on the entire power grid and improve power supply reliability. (3) Distributed power grid operation optimization methods can help promote the development of the renewable energy industry and promote the optimization and upgrading of the energy structure. At the same time, the price guidance mechanism can guide social resources to the renewable energy field and provide strong support for sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of the distributed power grid operation optimization steps of the present invention. DETAILED DESCRIPTION

[0017] 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.

[0018] See also Figure 1 The present invention provides a technical solution: a distributed power grid operation optimization method taking into account a price guidance mechanism, comprising the following steps: S1. Construct a price guidance mechanism model: collect real-time data of various distributed resources (such as distributed energy, energy storage devices, controllable loads, etc.) in the distributed power grid, and obtain electricity price information of the external power grid, including real-time electricity prices, time-of-use electricity prices, etc., and establish a price guidance model that reflects market price signals based on the collected data. At the same time, the model should be able to accurately reflect the changes in market supply and demand, as well as the response characteristics of distributed resources to price signals. In S1, a mathematical model of the distribution network is established to analyze the impact of the access of distributed power sources to the distribution network on voltage stability, and by analyzing the comprehensive demand response characteristics of the load side, the dispatchable resources on the load side are introduced into the distribution network voltage coordination control. Secondly, the model is solved by the CPLEX solver in Matlab to obtain the output of each coordinated control device, energy storage and time-shiftable load participating in the distribution network voltage coordination control, so as to verify the feasibility of the method. Finally, by introducing a ladder-type carbon trading mechanism, a distribution network voltage coordination control model with low-carbon characteristics is formed, with the lowest network loss cost, the lowest interruptible load cost and the lowest carbon trading cost. This paper establishes the minimum objective function, proposes the optimization strategy of the voltage coordination control method of the distribution network containing distributed power sources, and combines the improved IEEE33 node system for simulation verification. In S1, the power flow calculation of the distribution network containing distributed power sources is carried out to analyze the impact of the access of distributed power sources on the fault section location of the distribution network. Based on the encoding method that can reflect the direction of the fault current, the switch function that can dynamically reflect the number of distributed power sources connected, and the fitness function with fault tolerance performance, a fault section location model of the distribution network containing distributed power sources is established. By introducing artificial intelligence algorithms (genetic algorithms, particle swarm algorithms, ant colony algorithms, etc.), the model is solved to form a fast and accurate segment method for single-point faults, multi-point faults and information distortion faults. In S1, an island partition model based on load level is established to divide the optimal island range for distributed power sources with independent power supply capabilities. An artificial intelligence algorithm is introduced to restore and reconstruct the network outside the island after the fault occurs. By reducing the scope of the solution space and improving the search rate, an efficient and reliable fault recovery and reconstruction method is formed. S2. Optimize the scheduling of distributed resources: According to the price signal provided by the price guidance model, adjust the power generation plan of distributed energy, and increase the power generation of distributed energy during the period of high electricity price; reduce the power generation or store energy during the period of low electricity price, and optimize the charging and discharging strategy of energy storage equipment according to the price signal, and charge during the period of low electricity price to store energy; discharge during the period of high electricity price to release energy and obtain economic benefits, and guide the controllable load to adjust its electricity consumption behavior through price signals, and reduce or transfer electricity consumption during the period of high electricity price; increase electricity consumption during the period of low electricity price. The key variables of the operation are taken as optimization variables, such as the output of distributed power sources, the charging and discharging strategies of energy storage equipment, and the scheduling of loads, and the corresponding objective functions are established according to the optimization objectives, such as minimizing the operating cost and maximizing the energy efficiency, and the physical constraints of the power grid (such as line capacity, voltage range, etc.) and the operation constraints (such as load demand, output limit of distributed power sources, etc.) are considered, and the corresponding constraints are set. In S2, according to the complexity and constraints of the optimization model, the appropriate optimization algorithm is selected, such as genetic algorithm, particle swarm algorithm, simulated annealing algorithm, etc., and the parameters of the selected optimization algorithm are configured, such as population size, number of iterations, crossover probability, mutation probability, etc.; S3, coordinated interactive response of distributed resources: Based on multi-agent theory or similar methods, a coordinated operation strategy between distributed resources is constructed. At the same time, distributed resource agents interact and respond to other resource agents according to their own needs and price signals, and set priorities for each distributed resource agent according to the size of the interactive benefits. At the same time, in each operating time period, the needs of each resource agent are responded to in order of priority. In S3, a transient characteristic analysis model of distributed power sources is established, and an analytical expression of fault current is obtained. The fault current characteristics of distributed power sources under various control strategies are compared and analyzed. Then, the fault ride-through control method of distributed power sources is studied, and the fault characteristics of distributed power sources are combined with the distribution network system level. In order to meet the needs of the power grid, a fast fault ride-through method is designed. In S3, photovoltaic, wind turbines and energy storage are connected to the AC bus through power electronic converters. The control strategies of power electronic converters mainly include constant current control, constant power control, constant voltage control and droop control. Constant current control and constant power control belong to current type control strategies, constant voltage control and droop control belong to voltage type control strategies. According to different scenarios and different operation modes of the distribution network containing DG, the appropriate converter control strategy is selected. In S3, DG is connected to the AC bus through an interface converter. In addition to being able to be connected to the grid, the distribution network containing high penetration DG can also operate in island mode. The DG switching control strategy continues to maintain the stable operation of the distribution network. S4. Establish a real-time monitoring system to monitor the operating status and interaction of various resources in the distributed power grid, and promptly discover and solve possible problems. By comparing the power grid operation data before and after optimization, evaluate the effect of the price guidance mechanism on the optimization of distributed power grid operation, and adjust and optimize the price guidance model and dispatch strategy based on the evaluation results. S5. Feedback and adjustment: Adjust and optimize the price guidance model and dispatch strategy based on user feedback and evaluation results, and continuously improve the operation optimization methods of distributed power grids.

[0019] Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A distributed power grid operation optimization method taking into account a price guidance mechanism comprises the following steps: S1. Construct a price guidance mechanism model: collect real-time data of various distributed resources (such as distributed energy, energy storage devices, controllable loads, etc.) in the distributed power grid, and obtain electricity price information of the external power grid, including real-time electricity price, time-of-use electricity price, etc., and establish a price guidance model that reflects market price signals based on the collected data. At the same time, the model should be able to accurately reflect the changes in market supply and demand, as well as the response characteristics of distributed resources to price signals; S2. Optimize the scheduling of distributed resources: According to the price signals provided by the price guidance model, adjust the power generation plan of distributed energy, and increase the power generation of distributed energy during the period of high electricity prices; reduce the power generation or store energy during the period of low electricity prices, and optimize the charging and discharging strategy of energy storage equipment according to price signals, and charge during the period of low electricity prices to store energy; discharge during the period of high electricity prices to release energy and obtain economic benefits, and guide the controllable load to adjust its electricity consumption behavior through price signals, and reduce or transfer electricity consumption during the period of high electricity prices; increase electricity consumption during the period of low electricity prices; S3. Coordinated interactive response of distributed resources: Based on multi-agent theory or similar methods, a coordinated operation strategy among distributed resources is constructed. At the same time, distributed resource agents interact and respond to other resource agents according to their own needs and price signals, and set priorities for each distributed resource agent according to the size of the interactive benefits. At the same time, in each operating time period, the needs of each resource agent are responded to in order of priority; S4. Establish a real-time monitoring system to monitor the operating status and interaction of various resources in the distributed power grid, and promptly discover and solve possible problems. By comparing the power grid operation data before and after optimization, evaluate the effect of the price guidance mechanism on the optimization of distributed power grid operation, and adjust and optimize the price guidance model and dispatch strategy based on the evaluation results. S5. Feedback and adjustment: Adjust and optimize the price guidance model and dispatch strategy based on user feedback and evaluation results, and continuously improve the operation optimization methods of distributed power grids.

2. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In the S1, a mathematical model of the distribution network is established to analyze the impact of the access of distributed power sources to the distribution network on voltage stability, and the load-side dispatchable resources are introduced into the distribution network voltage coordination control by analyzing the comprehensive demand response characteristics of the load side. Secondly, the model is solved by the CPLEX solver in Matlab to obtain the output of each coordinated control device, energy storage and time-shiftable load participating in the distribution network voltage coordination control, so as to verify the feasibility of the method. Finally, a distribution network voltage coordination control model with low-carbon characteristics is formed by introducing a step-type carbon trading mechanism. The objective function is established with the lowest network loss cost, the lowest interruptible load cost and the lowest carbon trading cost, and an optimization strategy for the distribution network voltage coordination control method containing distributed power sources is proposed, which is simulated and verified in combination with the improved IEEE33 node system.

3. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In the S1, the power flow calculation is performed on the distribution network containing distributed power, and the influence of the access of distributed power sources on the fault section location of the distribution network is analyzed. Based on the coding method that can reflect the direction of the fault current, the switching function that can dynamically reflect the number of distributed power sources accessed, and the fitness function with fault-tolerant performance, a fault section location model of the distribution network containing distributed power sources is established. By introducing artificial intelligence algorithms (genetic algorithms, particle swarm algorithms, ant colony algorithms, etc.), the model is solved to form a fast and accurate section method for single-point faults, multi-point faults and information distortion faults.

4. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In the S1, an island partition model based on load level is established to optimally divide the range of distributed power sources with independent power supply capabilities, and an artificial intelligence algorithm is introduced to restore and reconstruct the network outside the island after a fault occurs. By reducing the scope of the solution space and improving the search rate, an efficient and reliable fault recovery and reconstruction method is formed.

5. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In S2, key variables that affect the operation of the power grid are selected as optimization variables, such as the output of distributed power sources, the charging and discharging strategies of energy storage equipment, and the scheduling of loads, and corresponding objective functions are established according to the optimization goals, such as minimizing operating costs, maximizing energy efficiency, etc., and considering the physical constraints of the power grid (such as line capacity, voltage range, etc.) and operating constraints (such as load demand, output limit of distributed power sources, etc.), corresponding constraints are set.

6. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In S2, a suitable optimization algorithm is selected according to the complexity and constraints of the optimization model, such as a genetic algorithm, a particle swarm algorithm, a simulated annealing algorithm, etc., and parameters of the selected optimization algorithm are configured, such as population size, number of iterations, crossover probability, mutation probability, etc.

7. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In the S3, a transient characteristic analysis model of distributed power sources is established, an analytical expression of fault current is obtained, and the fault current characteristics of distributed power sources under various control strategies are compared and analyzed. Then, the fault ride-through control method of distributed power sources is studied, and a fast fault ride-through method is designed by combining the fault characteristics of distributed power sources with the requirements of the distribution network system level.

8. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: In S3, photovoltaic, wind turbine and energy storage are connected to the AC bus through power electronic converters, wherein the control strategies of power electronic converters mainly include constant current control, constant power control, constant voltage control and droop control, wherein constant current control and constant power control belong to current type control strategies, constant voltage control and droop control belong to voltage type control strategies, and appropriate converter control strategies are selected according to different scenarios and different operation modes of the distribution network containing DG.

9. A distributed power grid operation optimization method taking into account a price guidance mechanism according to claim 1, characterized in that: The DG in S3 is connected to the AC bus through an interface converter. In addition to being able to be grid-connected, the distribution network containing high-penetration DG can also operate in an island mode, in which the DG switching control strategy continues to maintain the stable operation of the distribution network.

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