Optimized dispatching method for alternating current and direct current hybrid power grid

Abstract

An optimal scheduling method for an AC / DC hybrid power grid belongs to the field of power grids, and comprises the following steps: step 1, building the AC / DC hybrid power grid; 2, establishing an economic dispatching model of the alternating current and direct current hybrid power grid; 3, determining an optimization target of the AC / DC hybrid power grid; and step 4, optimizing scheduling. According to the invention, the operation stability and reliability of the AC-DC hybrid power grid are improved.

Description

Technical Field

[0001] The present invention relates to the field of power grids, and particularly to an optimal scheduling method for an AC / DC hybrid power grid. Background Art

[0002] Globally, the continuous growth of energy demand and the urgent need for environmental protection have promoted the rapid development of power systems. Traditional alternating current power grids (AC) have always been the mainstream of power systems due to their mature technology, low cost, and high operating reliability. However, with the large-scale access of distributed energy sources (such as solar and wind energy), the rapid popularization of electric vehicles, and the progress of direct current transmission technology, the status of direct current power grids (DC) in modern power systems has become increasingly prominent. As a new type of power system structure, the AC / DC hybrid grid integrates the advantages of AC and DC power grids, providing new research directions and challenges for the optimal scheduling of power systems.

[0003] An AC / DC hybrid grid refers to a power grid structure in which both AC and DC networks exist simultaneously in the same power system and the electrical energy conversion and interconnection between the two are realized through conversion devices (such as converter stations and inverters). The core of this system lies in making full use of the respective advantages of AC and DC power grids to achieve the efficient, safe, and economic operation of the power system. After long-term development, the technology of AC power grids has become very mature, and various equipment and technical standards are relatively perfect. The AC power grid shows high reliability during long-term operation and has strong fault tolerance. Due to the mature technology, the construction and maintenance costs of AC power grids are relatively low.

[0004] The structural design of an AC / DC hybrid grid is the basis for its optimal scheduling. Researchers have conducted studies on aspects such as the grid's topological structure, the configuration of conversion devices, and the selection of access points to achieve the optimal design of the AC / DC hybrid grid, and these studies provide theoretical support for the reliable operation and efficient scheduling of the grid. The stability and security of an AC / DC hybrid grid are important guarantees for its operation. Researchers have studied the dynamic characteristics and fault response mechanisms of the system through the establishment of mathematical models and simulation analyses to ensure the stable operation and rapid recovery ability of the grid.

[0005] In response to the complexity and multi-objective optimization requirements of AC-DC hybrid power grids, researchers have proposed various optimization algorithms, including genetic algorithms, particle swarm optimization algorithms, ant colony algorithms, simulated annealing algorithms, etc. These algorithms exhibit different advantages in different application scenarios. By selecting the appropriate optimization algorithm, the efficiency and accuracy of scheduling can be effectively improved. The optimal scheduling of AC-DC hybrid power grids needs to consider the coordinated operation of both the AC and DC parts. The coordinated control strategy realizes the dynamic balance and optimal scheduling between the AC and DC networks by real-time monitoring and adjusting system parameters. These strategies include voltage control, power flow control, and frequency control, etc. By comprehensively applying various control means, the stability and efficiency of the system are ensured.

[0006] As a new type of power system structure, the AC-DC hybrid power grid combines the advantages of AC power grids and DC power grids, but there are still problems with operation stability. Through research on power grid structure design, energy management and optimal scheduling, stability and security analysis, and equipment technology development, improving the operation stability and reliability of the AC-DC hybrid power grid is an issue that needs to be solved in power grid operation. Summary of the Invention

[0007] The present invention is an optimal scheduling method for an AC-DC hybrid power grid, which improves the operation stability and reliability of the AC-DC hybrid power grid.

[0008] An optimal scheduling method for an AC-DC hybrid power grid includes the following steps:

[0009] Step 1: Build an AC-DC hybrid power grid;

[0010] Step 2: Establish an economic scheduling model for the AC-DC hybrid power grid;

[0011] Step 3: Determine the optimization objectives of the AC-DC hybrid power grid;

[0012] Step 4: Optimize the scheduling.

[0013] Optionally, in Step 1: Build an AC-DC hybrid power grid, specifically including: an AC power grid, a DC power grid, an AC-DC converter, a renewable energy power generation device, an energy storage device, and a load.

[0014] Optionally, the voltage, current, and power formulas of the AC power grid are:

[0015] V = V max sin(ωt)

[0016] I = I max sin(ωt)

[0017] P = V rms ·I rms ·cos(φ)

[0018] Among them, V and I are voltage and current respectively, V max and I max are the peak values of voltage and current, V rms and I rms are the effective values of voltage and current, ω is the angular frequency, t is the time, P is the power, and φ is the power factor angle;

[0019] The voltage and current formulas for the DC power grid are:

[0020] V DC = I DC ·R DC

[0021] P DC = V DC ·I DC

[0022] Among them, V DC is the DC voltage, I DC is the DC current, R DC is the DC resistance, and P DC is the DC power;

[0023] The conversion efficiency formula for the AC-DC converter is:

[0024]

[0025] Among them, η is the efficiency of the converter, P out is the output power, and P in is the input power;

[0026] The renewable energy power generation device includes a photovoltaic power generation system;

[0027] The photovoltaic power formula for the photovoltaic power generation system is:

[0028] P PV = V PV ·I PV

[0029] Among them, P PV is the power of the photovoltaic cell, V PV is the voltage of the photovoltaic cell, and I PV is the current of the photovoltaic cell;

[0030] The energy storage device includes a battery;

[0031] The battery energy formula is:

[0032] E = C·V

[0033] Among them, E is the energy of the energy storage system, C is the capacity of the battery, and V is the voltage of the battery;

[0034] The load includes residential load, industrial load and commercial load;

[0035] Load power demand formula:

[0036] P load =V load ·I load ·cos(φ)

[0037] Wherein, P load is the power demand of the load, V load is the voltage of the load, I load is the current of the load, and φ is the power factor angle.

[0038] Optionally, in step 2: establish an economic dispatch model for the AC-DC hybrid power grid. The goal of the economic dispatch model is to minimize the total cost of the system. The total cost includes generation cost, loss cost and environmental cost;

[0039] The generation cost C total-f is: Suppose there are N generator sets, and the generation cost function C i (P i ) represents the generation cost of the i-th generator set, where P i is the generation power of the i-th generator set:

[0040]

[0041] The loss cost is related to the power loss in the power grid. The power loss L ij can be expressed by the resistance R ij of the line and the power flow P ij :

[0042]

[0043] The total loss cost C loss is the sum of all line losses:

[0044]

[0045] The environmental cost is usually related to emissions. The emission amount E i is proportional to the power generation amount P i ; The environmental cost function C env can be expressed as:

[0046]

[0047] Wherein, α i is the environmental cost coefficient of the i-th generator set, and E i =β i ·Pi Emissions caused by power generation

[0048] Comprehensive objective function C total Is the sum of power generation cost, loss cost and environmental cost:

[0049]

[0050] The economic dispatch model is expressed as:

[0051]

[0052] Optionally, the economic dispatch model needs to satisfy constraint conditions, and the constraint conditions include power balance, power limit, voltage limit and equipment operation constraints.

[0053] Optionally, the power balance is: for node k, the relationship between the total power generation and load power is:

[0054]

[0055] Where, P i And L j Are the power generation power and load power of nodes i and j respectively, and Generators, Loads and Lines are the sets of power plants, loads and lines respectively;

[0056] The power generation power of each generator set i needs to be within its minimum P i,min And maximum power P i,max Output range:

[0057] P i,min ≤P i ≤P i,max

[0058] The power flow of each transmission line also needs to satisfy its lower limit P ij,min And upper limit P ij,max :

[0059] P ij,min ≤P ij ≤P ij,max

[0060] The voltage of each node must be within the lower limit V k,min And upper limit V k,max To ensure the stability of the power grid; for node k, the voltage V k Range is:

[0061] V k,min ≤V k ≤V k,max

[0062] The charging power P of the energy storage device charge and the discharging power P discharge should satisfy its minimum P charge,min and P discharge,min and the maximum power P charge,max and P discharge,max range:

[0063] P charge,min ≤ P charge ≤ P charge,max ,

[0064] P discharge,min ≤ P discharge ≤ P discharge,max .

[0065] Optionally, step 3: Determine the optimization objectives of the AC-DC hybrid power grid, including: reducing generation costs, transmission losses, and operation and maintenance costs, maximizing energy efficiency, improving power transmission and conversion efficiency, reducing energy waste, enhancing system reliability, reducing power outage risks, maximizing environmental benefits, and reducing carbon emissions.

[0066] Optionally, the generation cost is C gen , and for the i-th generator set, its generation cost function is C i (P i ), where P i is the generation power:

[0067]

[0068] The total transmission loss C loss is the sum of all line losses:

[0069]

[0070] The total operation and maintenance cost C om is the sum of the operation and maintenance costs of all equipment:

[0071]

[0072] where C com,k is the operation and maintenance cost of the k-th equipment;

[0073] Maximizing energy efficiency means that the power transmission efficiency is improved by reducing transmission losses and optimizing the power flow. The transmission efficiency η trans is the ratio of the transmission power to the transmission loss:

[0074]

[0075] The power transmission and conversion efficiency involves the efficiency of the AC-DC converter, P transis the transmission power, and η is the efficiency of the converter conv is the output power P out and the input power P in ratio:

[0076]

[0077] System reliability includes voltage stability. Voltage stability analysis uses node voltage constraints:

[0078] V k,min ≤V k ≤V k,max

[0079] Power outage risk analysis involves system fault troubleshooting and backup measures. Power outage risk can be measured by the reliability index of the system, and the system reliability index R:

[0080]

[0081] Maximizing environmental benefits aims to increase the utilization ratio of renewable energy, reduce carbon emissions and environmental pollution. The utilization ratio β of renewable energy is expressed as:

[0082]

[0083] where P renewable is the power generation of renewable energy, and P total is the total power generation;

[0084] The carbon emission E is expressed as the product of the power generation and the emission factor:

[0085]

[0086] where β i is the emission factor of the i-th generator set.

[0087] Optionally, step 4: optimization scheduling includes selecting an optimization algorithm to optimize the grid scheduling.

[0088] Optionally, the optimization algorithm is a genetic algorithm, and the optimization steps are as follows:

[0089] Initialization: Generate an initial population Initial Population, where each individual Chromosome n (chromosome) represents a possible solution;

[0090] Initial Population={Chromosome1,Chromosome2,…,Chromosome n}

[0091] Among them, Chromosome: represents a possible solution and is the encoded representation of problem variables; Initial Population: represents a set composed of multiple chromosomes, and the initial population is the starting point for the genetic algorithm search;

[0092] Fitness evaluation: Calculate the fitness value of each individual; the fitness value reflects the performance of this individual in solving the optimization problem; the fitness function Fitness(Chromosome) is the value of the objective function Objective Function Value;

[0093] Fitness(Chromosome) = Objective Function Value

[0094] Among them, Fitness (fitness): represents the quality of each chromosome, measured by the objective function value; Objective Function: a function used to evaluate the quality of solutions;

[0095] Selection: Select individuals for reproduction according to the fitness value, and high-quality individuals have a higher probability of being selected SelectionProbability ∝ Fitness Value;

[0096] Selection Probability ∝ Fitness Value

[0097] Among them, Selection: Select individuals for reproduction according to the fitness value; the higher the fitness value, the greater the probability of being selected;

[0098] Crossover: Pair the selected individuals for the crossover operation Crossover to generate new individuals Offspring n (offspring); the crossover operation usually involves exchanging a part of the content of the chromosome Parent n ;

[0099] Offspring1 = Crossover(Parent1,Parent2)

[0100] Offspring2 = Crossover(Parent2,Parent1)

[0101] Among them, Crossover: Pair the selected individuals for the crossover operation to generate new offspring; Parent n : represents the number of the parent chromosome in the crossover operation; Offspringn : Represents the number of the cross-generated offspring chromosomes;

[0102] Mutation: Perform mutation operation on the generated offspring (Mutated Offspring) to increase the diversity of the population and avoid falling into local optimum:

[0103] Mutated Offspring = Mutation(Offspring)

[0104] Among them, Mutation (mutation): Perform mutation operation (Mutated Offspring) on the generated offspring to increase the diversity of the population and avoid falling into local optimum solution;

[0105] Replacement: Replace part or all of the individuals in the population with the offspring to form a new population (NewPopulation) for the next round of iteration;

[0106] New Population = Replacement(Old Population, Offspring)

[0107] Among them, Replacement (replacement): Replacement strategy, replace part or all of the individuals in the population with the offspring to generate a new population for the next round of iteration; Old Population (old population): The current population, that is, the set of chromosomes containing the previous generation; Offspring (offspring): The set of new chromosomes generated through selection, crossover, and mutation operations; New Population (new population): The population formed after the replacement operation, containing the replaced individuals, as the basis population for the next round of iteration;

[0108] Termination condition: When the maximum number of iterations or fitness value is met, stop the optimization and return the best solution or optimal solution.

[0109] Beneficial effects:

[0110] The research method of AC-DC hybrid power grid based on optimal scheduling of the present invention solves the complex multi-objective optimization problem in the AC-DC hybrid power grid and improves the economy, reliability and utilization rate of renewable energy of the system. Description of the Drawings

[0111] Figure 1 It is the Pareto chart of the embodiment of the present invention.

[0112] Figure 2 It is the power curve of each device in the embodiment of the present invention.

[0113] Figure 3 This is a schematic diagram of the operating cost of the embodiments of the present invention. Detailed implementation manners

[0114] To describe the present invention more specifically, the following further explains the present invention with reference to the accompanying drawings and specific implementation cases.

[0115] An optimal scheduling method for an AC / DC hybrid power grid includes the following steps:

[0116] Step 1: Build an AC / DC hybrid power grid, including: an AC power transmission network, DC power transmission lines, AC / DC converters, renewable energy power generation devices (such as photovoltaic and wind energy), energy storage devices (such as battery energy storage systems), and loads (such as residential, industrial, and commercial loads).

[0117] This hybrid power grid utilizes the respective advantages of AC and DC to achieve efficient power transmission and flexible scheduling of electric energy, supports the access of large-scale renewable energy, and improves the stability and reliability of the system.

[0118] An AC / DC hybrid grid is a power system structure that integrates an AC power grid (AC) and a DC power grid (DC). It interconnects the AC and DC networks through AC / DC converters to achieve efficient conversion of electric energy between the two networks. This hybrid grid combines the advantages of AC and DC power grids to improve the transmission efficiency of the power system, support the access of large-scale renewable energy, and enhance the stability and reliability of the system.

[0119] The AC power transmission network is a main component of the power system. Its main feature is to transmit and distribute electric power in the form of alternating current. The composition of the AC power grid includes power plants, substations, power transmission lines, and distribution networks, etc. The AC power grid has the advantages of mature technology, stable operation, and low cost, but there is a problem of relatively large energy loss during long-distance power transmission.

[0120] The voltage, current, and power formulas of the AC power grid are:

[0121] V = V max sin(ωt)

[0122] I = I max sin(ωt)

[0123] P = V rms ·I rms ·cos(φ)

[0124] Wherein, V and I are the voltage and current respectively, V max and I max are the peak values of the voltage and current, V rms and Irms V and I are the effective values of voltage and current, ω is the angular frequency, t is the time, P is the power, and φ is the power factor angle.

[0125] HVDC transmission lines are used for long-distance and high-efficiency power transmission, which can reduce power losses during the transmission process. The composition of a DC power grid includes DC power generation devices, converter stations, HVDC transmission lines, and DC distribution grids, etc. HVDC transmission has significant advantages in large-capacity and long-distance transmission, and can better support the access of renewable energy.

[0126] Voltage and current formulas for a DC power grid

[0127] V DC = I DC ·R DC

[0128] P DC = V DC ·I DC

[0129] Among them, V DC is the DC voltage, I DC is the DC current, R DC is the DC resistance, and P DC is the DC power.

[0130] AC-DC converters are key devices connecting the AC power grid and the DC power grid, responsible for converting AC power to DC power, or converting DC power to AC power. It mainly includes converter stations, converters, and inverters, etc. AC-DC converters enable two power grids to achieve bidirectional power flow and mutual conversion, thus realizing the optimal dispatching and energy management of the power grid.

[0131] Conversion efficiency formula of AC-DC converters:

[0132]

[0133] Among them, η is the efficiency of the converter, P out is the output power, and P in is the input power.

[0134] Renewable energy power generation devices include photovoltaic power generation systems, wind power generation systems, etc. These devices use natural resources such as solar energy and wind energy for power production, which is not only environmentally friendly but also can reduce the dependence on fossil fuels. They usually generate electric power in the form of DC power, and need to convert the DC power to AC power through an inverter, or directly connect to the DC power grid.

[0135] Photovoltaic power formula:

[0136] P PV = V PV ·I PV

[0137] Among them, P PV is the power of the photovoltaic cell, V PV is the voltage of the photovoltaic cell, I PV is the current of the photovoltaic cell.

[0138] Energy storage devices (such as battery energy storage systems) are used to balance power supply and demand, store excess electrical energy, and release it when needed. Energy storage systems improve the flexibility and reliability of the power grid, especially in the integration of variable energy sources such as wind and solar energy.

[0139] Battery energy formula:

[0140] E = C·V

[0141] Among them, E is the energy of the energy storage system, C is the capacity of the battery, and V is the voltage of the battery.

[0142] Loads include residential loads, industrial loads, and commercial loads, etc. The demand characteristics of loads have an important impact on the operation of the power grid. Through flexible scheduling and optimization, the AC-DC hybrid power grid can balance the demands of different loads and improve the overall efficiency and stability of the power grid.

[0143] Load power demand formula:

[0144] P load = V load ·I load ·cos(φ)

[0145] Among them, P load is the power demand of the load, V load is the voltage of the load, I load is the current of the load, and φ is the power factor angle.

[0146] The advantages of this hybrid power grid make it play an increasingly important role in modern power systems, providing a solid foundation for the optimal scheduling and sustainable development of power systems.

[0147] Step 2: Establish an economic dispatch model for the AC-DC hybrid power grid, including: determining the economic dispatch objective function, such as minimizing generation cost, loss cost, and environmental cost, and defining power balance, power limit, voltage limit, and equipment operation constraints.

[0148] The objective of economic dispatch is to minimize the total cost of the system, and the total cost includes generation cost, loss cost, and environmental cost.

[0149] Generation cost is usually one of the most important economic costs. Suppose there are N generating units, and the generation cost function C i (P i) represents the power generation cost of the i-th generator set, where P i is the power generation power of the i-th generator set.

[0150]

[0151] The loss cost is related to the power loss in the power grid, and the loss can be used to describe the loss in power transmission. The power loss L ij can be expressed by the resistance R of the line ij and the power flow P ij .

[0152]

[0153] The total loss cost C loss is the sum of all line losses:

[0154]

[0155] The environmental cost is usually related to emissions. Assuming the emissions E i is proportional to the power generation P i . The environmental cost function C env can be expressed as:

[0156]

[0157] where α i is the environmental cost coefficient of the i-th generator set, and E i = β i ·P i is the emissions caused by the power generation.

[0158] The comprehensive objective function C total is the sum of the power generation cost, the loss cost, and the environmental cost:

[0159]

[0160] The economic dispatch model needs to satisfy a series of constraints, including power balance, power limit, voltage limit, and equipment operation constraints, etc.

[0161] The power balance constraint requires the balance between all power generation and load. For the relationship between the total power generation and load power at node k:

[0162]

[0163] where P i and L j are the power generation and load power of nodes i and j respectively.

[0164] The power generation of each generator set i needs to be within its minimum P i,min and maximum power P i,max output range:

[0165] P i,min ≤ P i ≤ P i,max

[0166] The power flow of each transmission line also needs to satisfy its lower limit P ij,min and upper limit P ij,max :

[0167] P ij,min ≤ P ij ≤ P ij,max

[0168] The voltage of each node must be within the lower limit V k,min and upper limit V k,max to ensure the stability of the power grid. For node k, the voltage V k range is:

[0169] V k,min ≤ V k ≤ V k,max

[0170] The operation of AC-DC converters and energy storage devices also needs to satisfy corresponding constraints. For example, the charging and discharging power of the energy storage device should satisfy its minimum P charge,min and P discharge,min and maximum power P charge,max and P discharge,max range:

[0171] P charge,min ≤ P charge ≤ P charge,max

[0172] P discharge,min ≤ P discharge ≤ P discharge,max

[0173] Taking into account the above objective function and constraints, the economic dispatch model can be expressed as:

[0174]

[0175] By solving the above optimization problem, the economic dispatch of the AC-DC hybrid power grid can be achieved to minimize the total economic cost while satisfying the various constraints of the power system.

[0176] Step 3: Determine the optimization objectives of the AC-DC hybrid power grid, including: minimizing economic costs, reducing generation costs, transmission losses, and operation and maintenance expenses; maximizing energy efficiency, improving the efficiency of power transmission and conversion, reducing energy waste; enhancing system reliability, ensuring the stability and security of the power grid under various operating conditions, and reducing the risk of power outages; maximizing environmental benefits, increasing the utilization of renewable energy, and reducing carbon emissions and environmental pollution.

[0177] Minimizing economic costs is the core objective of optimizing the AC-DC hybrid power grid, which involves reducing generation costs, transmission losses, and operation and maintenance expenses.

[0178] Generation cost C gen Generally includes fuel costs, operation and maintenance costs, etc. For the i-th generator set, its generation cost function is C i (P i ), where P i is the generation power.

[0179]

[0180] Among them, C i (P i ) can be represented by a linear or non-linear function, usually a function of the generation power

[0181] Transmission losses are related to the power flow and line resistance. For the transmission line (i,j), its loss L ij is calculated by the following formula:

[0182]

[0183] The total transmission loss C loss is the sum of all line losses:

[0184]

[0185] Operation and maintenance expenses include equipment maintenance, labor costs, and other operating expenditures. The total operation and maintenance expense C om is the sum of the operation and maintenance expenses of all equipment:

[0186]

[0187] Among them, C com,k is the operation and maintenance expense of the k-th equipment.

[0188] Maximizing energy efficiency aims to improve the efficiency of power transmission and conversion and reduce energy waste.

[0189] The power transmission efficiency is improved by reducing transmission losses and optimizing the power flow. The transmission efficiency η trans is the ratio of the transmission power to the transmission loss:

[0190]

[0191] The conversion efficiency involves the efficiency of the AC-DC converter, where P trans is the transmission power, and the efficiency η of the converter conv is the output power P out and the ratio of the input power P in :

[0192]

[0193] Improving system reliability ensures the stability and security of the power grid under various operating conditions and reduces the risk of power outages.

[0194] The stability analysis of the system includes voltage stability and frequency stability. Voltage stability analysis can use the node voltage constraint:

[0195] V k,min ≤V k ≤V k,max

[0196] Power outage risk analysis involves system fault diagnosis and backup measures. The power outage risk can be measured by the reliability index of the system, such as the system reliability index R:

[0197]

[0198] Maximizing environmental benefits aims to increase the utilization of renewable energy, reduce carbon emissions and environmental pollution.

[0199] The utilization ratio β of renewable energy can be expressed as:

[0200]

[0201] where P renewanle is the power generation of renewable energy, and P total is the total power generation.

[0202] Reducing carbon emissions can be achieved by optimizing the power generation mix. The carbon emission E can be expressed as the product of the power generation and the emission factor:

[0203]

[0204] where β i is the emission factor of the i-th generator set.

[0205] By optimizing these objectives, the comprehensive improvement of the economic, environmental and system benefits of the AC-DC hybrid power grid can be achieved.

[0206] Step 4: Optimize the scheduling, including: Selecting a suitable optimization algorithm, namely the genetic algorithm, to effectively solve the power grid scheduling problem.

[0207] The Genetic Algorithm (GA) is an optimization algorithm that simulates natural selection and genetic mechanisms. Its core idea is to find the optimal solution to the problem by simulating the selection, crossover, and mutation operations in the biological evolution process. The genetic algorithm is a global optimization algorithm and is suitable for complex optimization problems, including power grid scheduling problems.

[0208] The basic steps of the genetic algorithm are as follows:

[0209] Initialization: Generate an initial population, Initial Population, where each individual Chromosome n (chromosome) represents a possible solution.

[0210] Initial Population = {Chromosome1, Chromosome2, …, Chromosome n}

[0211] Among them, Chromosome (chromosome): represents a possible solution and is the encoded representation of the problem variables; Initial Population (initial population): represents a set composed of multiple chromosomes, and the initial population is the starting point for the genetic algorithm search.

[0212] Fitness evaluation: Calculate the fitness value of each individual. The fitness value reflects the performance of this individual in solving the optimization problem. The fitness function Fitness(Chromosome) is the value of the objective function, Objective Function Value.

[0213] Fitness(Chromosome) = Objective Function Value

[0214] Among them, Fitness (fitness): represents the quality of each chromosome, measured by the objective function value. Objective Function (objective function): a function used to evaluate the quality of the solution.

[0215] Selection: Select individuals for reproduction based on the fitness value. High-quality individuals have a higher probability of being selected, SelectionProbability ∝ Fitness Value. Commonly used selection strategies include roulette wheel selection, tournament selection, etc.

[0216] Selection Probability ∝ Fitness Value

[0217] Among them, Selection: Select individuals according to the fitness value for reproduction. The higher the fitness value, the greater the probability of being selected.

[0218] Crossover: Pair the selected individuals to perform the crossover operation Crossover to generate new individuals Offspring n (offspring). The crossover operation usually involves exchanging parts of the chromosomes Parent n content.

[0219] Offspring1 = Crossover(Parent1, Parent2)

[0220] Offspring2 = Crossover(Parent2, Parent1)

[0221] Among them, Crossover: Pair the selected individuals to perform the crossover operation to generate new offspring; Parent n : Represents the number of the parental chromosome in the crossover operation; Offspring n : Represents the number of the offspring chromosome generated by crossover.

[0222] Mutation: Perform the mutation operation Mutated Offspring on the generated offspring to increase the diversity of the population and avoid falling into local optima:

[0223] Mutated Offspring = Mutation(Offspring)

[0224] Among them, Mutation: Perform the mutation operation (Mutated Offspring) on the generated offspring to increase the diversity of the population and avoid falling into the local optimal solution.

[0225] Replacement: Replace part or all of the individuals in the population with the offspring to form a new population NewPopulation for the next round of iteration.

[0226] New Population = Replacement(Old Population, Offspring)

[0227] Among them, Replacement: The replacement strategy is to replace some or all individuals in the population with offspring to generate a new population for the next iteration. Old Population: The current population, that is, the set of chromosomes containing the previous generation. Offspring: The new set of chromosomes generated through the operations of Selection, Crossover, and Mutation. New Population: The population formed after the replacement operation, containing the replaced individuals, which serves as the basis population for the next iteration.

[0228] Termination condition: When the termination condition is met (such as reaching the maximum number of iterations or the fitness value is good enough), the algorithm stops and returns the best solution or the optimal solution.

[0229] Case study, specifically including: creating a specific AC-DC hybrid power grid model and using the aforementioned optimization algorithm to solve and analyze it.

[0230] To conduct a case study, an AC-DC hybrid power grid model is constructed. The model includes: AC power grid: consisting of generator sets, loads, and transmission lines. DC power grid: consisting of DC power generation devices, energy storage devices, and DC loads. AC-DC converters: connecting the AC power grid and the DC power grid.

[0231] AC power grid: Generator sets: 3 generator sets, Transmission lines: 2 transmission lines, Loads: 2 load nodes, DC power grid: DC power generation devices: 1, Energy storage devices: 1, DC loads: 1, AC-DC converters: Converters: 1.

[0232] Figure 1 It is a Pareto chart. All the red dots in the chart represent the trade-offs among the three objectives of economy, environmental protection, and inclusiveness. These points may form the Pareto front, indicating that these solutions are optimal when no single solution is better than others in all objectives simultaneously.

[0233] Figure 2The following is the electrical load curve before and after demand response, showing the power variations of four different energy devices over a period of time. Fuel cell: The overall power is relatively low with small fluctuations, and most of the power values are between 0 and 20. Energy storage: The power change is the smallest, being relatively stable overall, and the power values mostly fluctuate between -10 and 10. Micro gas turbine: The power fluctuates greatly, with frequent up and down fluctuations, and most of the power values are between 0 and 40. Combustion generator: The power fluctuates the most and has the widest range of variation, and most of the power values are between 0 and 80. The four energy devices in the system play their respective roles at different time periods. The combustion generator and micro gas turbine mainly respond to large load demand fluctuations. The energy storage device may store energy when the power demand is low and release energy when the demand is high to smooth the overall power output. The fuel cell may be used to provide a stable base load to maintain the basic operation of the system.

[0234] Figure 3 The following is the operating cost, showing the changes in the operating cost of a system over different time periods. Peak cost: The peaks that occur at times 4, 10, and 15 may be related to high load demands in the system or the startup of some high-energy-consuming devices. The periodic fluctuations in the operating cost may be related to the operating cycles of the devices in the system or the periodic changes in the load demand. Near time periods 8, 12, and 20, the operating cost is relatively low, possibly due to a decrease in load demand or the operation of efficient devices.

[0235] The present invention discloses an optimal scheduling method for a hybrid AC / DC power grid. As an important development direction of modern power systems, the hybrid AC / DC power grid realizes more efficient and flexible power transmission and distribution by integrating the advantages of AC and DC power grids. The present invention proposes a research method for a hybrid AC / DC power grid based on optimal scheduling, aiming to solve the complex multi-objective optimization problems in the power grid and improve the economy, reliability, and utilization rate of renewable energy of the system. First, a mathematical model of the hybrid AC / DC power grid is established, covering key components such as AC / DC converters, renewable energy access, energy storage devices, and loads, considering the physical constraints and operating characteristics of the power grid; secondly, a hybrid optimization algorithm is used to solve the scheduling optimization problem to achieve the dynamic scheduling optimization of the AC / DC power grid and improve the overall efficiency of the system. Finally, the effectiveness of the proposed method is verified by simulation, and the operating states of the power grid before and after optimal scheduling are analyzed.

Claims

1. An optimal scheduling method for an AC / DC hybrid power grid, characterized in that It includes the following steps: Step 1: Build an AC-DC hybrid power grid; Step 2: Establish an economic dispatch model for the AC-DC hybrid power grid; Step 3: Determine the optimization objectives of the AC-DC hybrid power grid; Step 4: Optimize the dispatch.

2. The method according to claim 1, wherein Step 1: Build an AC-DC hybrid power grid, specifically including: an AC power grid, a DC power grid, an AC-DC converter, a renewable energy power generation device, an energy storage device, and a load.

3. The method according to claim 2, wherein The voltage, current, and power formulas of the AC power grid are: V = V max sin(ωt) I = I max sin(ωt) P = V rms ·I rms ·cos(φ) where V and I are voltage and current respectively, V max and I max are the peak values of voltage and current, V rms and I rms are the effective values of voltage and current, ω is the angular frequency, t is time, P is power, and φ is the power factor angle; The voltage and current formulas of the DC power grid are: V DC = I DC · R DC P DC = V DC · I DC Among them, V DC is the DC voltage, I DC is the DC current, R DC is the DC resistance, P DC is the DC power; The conversion efficiency formula of the AC-DC converter is: Among them, η is the efficiency of the converter, P out is the output power, P in is the input power; The renewable energy power generation device includes a photovoltaic power generation system; The photovoltaic power formula of the photovoltaic power generation system is: P PV = V PV · I PV Among them, P PV is the power of the photovoltaic cell, V PV is the voltage of the photovoltaic cell, I PV is the current of the photovoltaic cell; The energy storage device includes a battery; The battery energy formula is: E = C·V Wherein, E is the energy of the energy storage system, C is the capacity of the battery, and V is the voltage of the battery; The load includes residential load, industrial load, and commercial load; The load power demand formula: P load = V load · I load · cos(φ) Among them, P load is the power demand of the load, V load is the voltage of the load, I load is the current of the load, and φ is the power factor angle.

4. The method according to claim 1, wherein The said Step 2: Establish an economic dispatch model for the AC-DC hybrid power grid. The goal of the economic dispatch model is to minimize the total cost of the system. The total cost includes generation cost, loss cost, and environmental cost; Power generation cost C total-f is as follows: Suppose there are N generator sets, and the power generation cost function C i (P i ) represents the power generation cost of the i-th generator set, where P i is the power generation power of the i-th generator set: The loss cost is related to the power loss in the power grid, and the power loss L ij can be represented by the resistance R of the line ik and the power flow P ij as follows: Total loss cost C loss Is the sum of all line losses: Environmental costs are usually related to emissions, with the emission volume E i being proportional to the power generation volume P i ; the environmental cost function C env can be expressed as: Among them, α i is the environmental cost coefficient of the i-th generating unit, and E i = β i ·P i is the emission caused by the power generation; Comprehensive objective function C total It is the sum of the power generation cost, loss cost, and environmental cost: The economic dispatch model is expressed as:

5. The method according to claim 4, wherein The economic dispatch model needs to satisfy constraint conditions. The said constraint conditions include power balance, power limit, voltage limit, and equipment operation constraints.

6. The method according to claim 5, wherein The power balance is: For node k, the relationship between the total generation power and the load power is: Among them, P i and L j are the power generation power and load power of nodes i and j respectively, and Generators, Loads, and Lines are the sets of power plants, loads, and lines respectively; The generated power of each generator set i needs to be within its minimum P i,min and maximum power P i,max output range: P i,min ≤P i ≤P i,max The power flow of each transmission line also needs to satisfy the lower limit P of its transmission capacity ij,min and the upper limit P ij,max : P ij,min ≤P ij ≤P ij,max The voltage of each node must be within the lower limit V k,min and the upper limit V k,max to ensure the stability of the power grid; for the voltage Vk k of node k, the range is: V k,min ≤V k ≤V k,max The charging power P of the energy storage device charge and the discharging power P discharge should satisfy its minimum P charge,min and P discharge,min and the maximum power P charge,max and P discharge,max Range: P charge,min ≤P charge ≤P charge,max , P discharge,min ≤P discharge ≤P discharge,max 。 7. The method according to claim 1, wherein The said Step 3: Determine the optimization objectives of the AC-DC hybrid power grid, including: reducing generation cost, transmission loss, and operation and maintenance cost, maximizing energy efficiency, improving power transmission and conversion efficiency, reducing energy waste, enhancing system reliability, reducing power outage risk, maximizing environmental benefits, and reducing carbon emissions.

8. The method according to claim 7, wherein The power generation cost is C gen , for the i-th generator set, its power generation cost function is C i (P i ), where P i is the power generation power: Total transmission loss C loss It is the sum of all line losses: Total operation and maintenance cost C om is the sum of the operation and maintenance costs of all devices: Among them, C com,k is the operation and maintenance cost of the k-th device; Maximizing energy efficiency means improving the power transmission efficiency of electricity by reducing transmission losses and optimizing power flow. The transmission efficiency η trans is the ratio of the transmitted power to the transmission losses: The electric energy transmission and conversion efficiency involves the efficiency of AC-DC converters. P teabs is the transmission power, and the efficiency η of the converter conv is the ratio of the output power P out to the input power P in : System reliability includes voltage stability. Voltage stability analysis uses node voltage constraints: V k,min ≤V k ≤V k,max Power outage risk analysis involves system fault troubleshooting and backup measures. Power outage risk can be measured by the reliability index of the system. The system reliability index R: Maximizing environmental benefits aims to increase the utilization ratio of renewable energy, reduce carbon emissions and environmental pollution. The utilization ratio β of renewable energy is expressed as: Among them, P renewable is the renewable energy power generation, and P total is the total power generation; The carbon emission E is expressed as the product of the power generation and the emission factor: Among them, β i is the emission factor of the i-th generating unit.

9. The method according to claim 1, wherein The said Step 4: Optimize the dispatch, including selecting an optimization algorithm and optimizing the power grid dispatch.

10. The method according to claim 9, wherein The optimization algorithm is a genetic algorithm. The optimization steps are as follows: Initialization: Generate an initial population of individuals (chromosomes), where each individual (chromosome) represents a possible solution; n (chromosome) represents a possible solution; Initial Population={Chromosome1,Chromosome2,…,Chromosome n} Wherein, Chromosome (chromosome): represents a possible solution and is the encoded representation of the problem variables; Initial Population (initial population): represents a set composed of multiple chromosomes. The initial population is the starting point for the genetic algorithm search; Fitness evaluation: Calculate the fitness value of each individual; The fitness value reflects the performance of this individual in solving the optimization problem; The fitness function Fitness(Chromosome) is the value of the objective function Objective Function Value; Fitness(Chromosome) = Objective Function Value Among them, Fitness (fitness): represents the quality of each chromosome, measured by the objective function value; Objective Function (objective function): a function used to evaluate the quality of the solution; Selection: Select individuals for reproduction according to the fitness value. High-quality individuals have a higher probability of being selected. SelectionProbability ∝ Fitness Value; Selection Probability ∝ Fitness Value Among them, Selection (selection): Select individuals for reproduction according to the fitness value. The higher the fitness value, the greater the probability of being selected; Crossover: Pair the selected individuals to perform the crossover operation to generate new individuals (offspring); the crossover operation usually involves exchanging a part of the chromosomes of the parents. n (offspring); n ​ Offspring1 = Crossover(Parent1, Parent2) Offspring2 = Crossover(Parent2, Parent1) Among them, Crossover: Pair the selected individuals for crossover operation to generate new offspring; Parent n : Represents the number of the parent chromosome in the crossover operation; Offspring n : Represents the number of the offspring chromosome generated by crossover; Mutation: Perform mutation operation on the generated offspring (Mutated Offspring) to increase the diversity of the population and avoid falling into local optimum: Mutated Offspring = Mutation(Offspring) Among them, Mutation (mutation): Perform mutation operation on the generated offspring (Mutated Offspring) to increase the diversity of the population and avoid falling into the local optimum solution; Replacement: Replace some or all individuals in the population with the offspring to form a new population (NewPopulation) for the next round of iteration; New Population = Replacement(Old Population, Offspring) Among them, Replacement (replacement): a replacement strategy, replacing some or all individuals in the population with the offspring to generate a new population for the next round of iteration; Old Population (old population): the current population, that is, the set of chromosomes containing the previous generation; Offspring (offspring): the set of new chromosomes generated through selection (Selection), crossover (Crossover), and mutation (Mutation) operations; New Population (new population): the population formed after the replacement operation, containing the replaced individuals, serving as the basis population for the next round of iteration; Termination condition: When the maximum number of iterations or the fitness value is met, stop the optimization and return the best solution or the optimal solution.

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