A material storage and distribution park economic scheduling method and system based on multi-energy conversion

Abstract

The present invention relates to an economic dispatch method and system for a material storage and distribution park based on multi-energy conversion. The method comprises: constructing an economic dispatch objective function for the material storage and distribution park with the goal of obtaining minimum economic cost; establishing an electric-hydrogen conversion equipment model; establishing a hydrogen storage tank and energy storage system model; establishing energy trading constraints for the material storage and distribution park; obtaining typical scenarios of wind and solar power output; establishing a charging and discharging behavior model for a material storage and distribution vehicle; establishing an energy balance constraint for the material storage and distribution park; constructing an economic dispatch optimization model for the material storage and distribution park based on the economic dispatch objective function for the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints, the typical scenarios of wind and solar power output, and the charging and discharging behavior model for the material storage and distribution vehicle; solving the optimization model to obtain an optimal economic dispatch plan, thereby effectively reducing the operating costs of the material storage and distribution park.

Description

Technical Field

[0001] The present invention relates to the technical field of economic dispatching of material storage and distribution parks, and in particular to a method and system for economic dispatching of material storage and distribution parks based on multi-energy conversion. Background Art

[0002] Against the backdrop of rapid economic growth, the development of the material storage and distribution sector has also accelerated. New-generation information technologies such as big data, cloud computing, the Internet of Things, mobile internet, and artificial intelligence, based on 5G, are driving the intelligent development of material storage and distribution parks. Unlike traditional material storage and distribution parks, the new generation of material storage and distribution parks are equipped with a variety of energy supply equipment, energy conversion, and storage equipment to meet the diverse load demands within the park, forming a relatively self-contained micro-energy network. Furthermore, material storage and distribution parks can trade with external energy markets to avoid energy shortages that prevent load demand from being met, or energy surpluses that prevent full consumption. They can also leverage the time-varying nature of energy prices and use energy storage equipment for arbitrage, thereby reducing the operating costs of material storage and distribution parks.

[0003] With the increasing pressure of carbon reduction targets, the development of new energy vehicles has accelerated. Among them, vehicles used for material storage and distribution are at the forefront of the low-carbon transformation of transportation. Material storage and distribution vehicles within material storage and distribution parks are easily dispatched and have relatively stable driving characteristics, making them more suitable for replacing traditional fuel-powered vehicles with new energy sources such as electricity or hydrogen. After completing their distribution tasks, these vehicles can flexibly charge and discharge using renewable energy sources such as wind power and photovoltaics within the park, or hydrogen energy equipment such as electrolyzers and hydrogen storage tanks. This allows them to replenish energy before their next distribution task and participate in demand response within the distribution park, contributing to increased energy flexibility and reduced operating costs within the distribution park. Furthermore, as the scale of the distribution sector expands significantly, the use of new energy vehicles will save significant fossil energy and create significant economic, social, and environmental benefits.

[0004] In summary, the new generation of material storage and distribution parks is equipped with a large number of clean energy supply, conversion, storage, and transmission equipment, as well as a large number of intelligent material storage and distribution equipment such as new energy material storage and distribution vehicles, automatic conveyor belts, and robotic arms. If a large number of energy and intelligent devices operate in a disorderly mode without coordinated and optimized control, the daily operation costs of the material storage and distribution park will inevitably increase significantly. Therefore, the need to flexibly dispatch various equipment within the material storage and distribution park and propose optimized energy trading strategies to achieve the economic operation of the material storage and distribution park has emerged. Summary of the Invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide an economic dispatch method and system for a material storage and distribution park based on multi-energy conversion.

[0006] The present invention solves the technical problem by adopting the following technical solutions:

[0007] A method for economic dispatching of a material storage and distribution park based on multi-energy conversion, comprising:

[0008] Obtain historical output data of wind power and photovoltaic renewable energy within the material storage and distribution park, conventional load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, and market hydrogen price data;

[0009] The economic dispatch objective function of the material storage and distribution park is constructed with the goal of obtaining the minimum economic cost;

[0010] Establishing an electric-hydrogen conversion device model according to the parameters of the electric-hydrogen conversion device;

[0011] Establish a hydrogen storage tank and energy storage system model based on the parameters of the hydrogen storage tank and its energy storage system;

[0012] Establishing energy transaction constraints for the material storage and distribution park based on the market electricity price data and the market hydrogen price data;

[0013] Based on the historical output data of renewable energy sources such as wind power and photovoltaics, the scenario reduction method is used to obtain typical scenarios and corresponding probabilities of wind and solar output;

[0014] Based on the charging and discharging energy requirements of electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles, a charging and discharging behavior model of material storage and distribution vehicles is established;

[0015] Establish energy balance constraints for material storage and distribution parks based on energy transaction volume, equipment operating conditions, and conventional load data;

[0016] An economic dispatch optimization model for the material storage and distribution park is constructed based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints of the material storage and distribution park, the typical wind and solar output scenarios, and the charging and discharging behavior model of the material storage and distribution vehicle.

[0017] The economic dispatch optimization model of the material storage and distribution park is solved to obtain the optimal operating conditions of each equipment in the material storage and distribution park, the optimal trading strategies for the electricity market and the hydrogen market, and the optimal charging and discharging strategies for the material storage and distribution vehicles.

[0018] Moreover, the formula of the economic dispatch objective function of the resource storage and distribution park is:

[0019]

[0020] Where: T is all time periods in the scheduling period, the subscript t of each variable represents the value of the variable in time period t; Nsce is the number of typical scenarios, and the subscript ω represents the value of the variable in scenario ω; They are the day-ahead electricity purchase price, the real-time electricity purchase price and the real-time electricity sales price; They are the day-ahead hydrogen purchase price, real-time hydrogen purchase price and real-time hydrogen sales price; They are day-ahead electricity purchase power, real-time electricity purchase power, real-time electricity sales power, day-ahead hydrogen purchase volume, real-time hydrogen purchase volume, and real-time hydrogen sales volume; ρ ω is the probability of scenario ω occurring; the objective function includes the day-ahead electricity purchase cost, real-time net cost of electricity purchase and sale, day-ahead hydrogen purchase cost, and real-time net cost of hydrogen purchase and sale of the material storage and distribution park.

[0021] Moreover, the electricity-hydrogen conversion equipment includes two types: electrolyzers and fuel cells, both of which are installed in the material storage and distribution park. The electricity-hydrogen conversion equipment can perform multi-energy conversion of electricity and hydrogen energy, realizing a flexible operation mode of multi-energy complementarity; and the electricity-hydrogen conversion equipment model is:

[0022] H el，t，ω =η e1 P el，t，ω

[0023] P FC，t，ω =η FC H FC，t，ω

[0024] Among them, η el and η FC are the conversion rates of electrolyzer and fuel cell respectively; P el，t，ω and H el，t，ω are the electric power input to the electrolyzer and the hydrogen mass output; H FC，t，ω and P FC，t，ω are the hydrogen mass input to the fuel cell and the electrical power output;

[0025] Constraints of the electric-hydrogen conversion equipment model:

[0026] P el，min ≤P el，t，ω ≤P el，max

[0027] H FC，min ≤H FC，t，ω ≤H FC，max

[0028] Among them, P el，max 、P e1，min 、H FC，max 、H FC，minThey are the maximum input power of the electrolyzer, the minimum input power of the electrolyzer, the maximum hydrogen input of the fuel cell, and the minimum hydrogen input of the fuel cell.

[0029] Moreover, the hydrogen storage tank and energy storage system model is as follows:

[0030]

[0031] P com，min ≤P com，t，ω ≤P com，max

[0032]

[0033] S H，1，ω =S H，T，ω

[0034]

[0035]

[0036] S H，min ≤S H，t，ω ≤S H，max

[0037]

[0038]

[0039]

[0040]

[0041]

[0042] Among them, P com，t，ω is the electric power of the compressor; R H 、T in ,κ,η com and P out / P in are the specific heat capacity constant of hydrogen, the temperature of compressed hydrogen, the hydrogen isentropic index, the compressor efficiency and the compression ratio; P is the mass of hydrogen that needs to be stored in the hydrogen storage tank. com，max and P com，min is the maximum value of the compressor electric power and the minimum value of the compressor electric power; S H，t，ω is the mass of hydrogen stored in the hydrogen storage tank; The mass of hydrogen released from the hydrogen storage tank; A 0-1 variable that indicates the state of the hydrogen storage tank. When it is 1, it means that hydrogen is stored in the tank, and when it is 0, it means that hydrogen is taken out of the tank. and are the efficiency of storing and releasing hydrogen in the hydrogen storage tank respectively; are the maximum and minimum values of the hydrogen mass that can be stored in the hydrogen storage tank in each period and the maximum and minimum values of the hydrogen mass that can be released; S H，min and S H，max are the minimum and maximum values of the hydrogen quality in the hydrogen storage tank respectively; is the state of charge of the energy storage system; It is a 0-1 variable indicating the charge and discharge state. When it is 1, it indicates charging, and when it is 0, it indicates discharging. and are the charging and discharging power of the energy storage system respectively; and are the charging and discharging efficiency of the energy storage system; They are the maximum value of charging power, the minimum value of charging power, the maximum value of discharging power, and the minimum value of discharging power respectively; and are the maximum and minimum state of charge of the energy storage system, respectively.

[0043] Moreover, the energy trading constraints of the material storage and distribution park are:

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] in, and are 0-1 variables representing the real-time purchase and sale status of electricity and hydrogen respectively, where 1 indicates purchase of the corresponding energy and 0 indicates sale of the corresponding energy; They are the maximum and minimum values of electricity purchased the day before, the maximum and minimum values of hydrogen purchased the day before; They are respectively the maximum and minimum values of real-time electricity purchase power, the maximum and minimum values of real-time electricity sales power, the maximum and minimum values of real-time hydrogen purchase volume, and the maximum and minimum values of real-time hydrogen sales volume.

[0051] Moreover, the charging and discharging energy requirements of the electric material storage and distribution vehicle are the same as those of the hydrogen material storage and distribution vehicle, both of which include the charging and discharging start time of the material storage and distribution vehicle. Charging and discharging end time Energy state at the beginning of charging and discharging Expected state of charge at the end of charging and discharging The charging and discharging energy behavior model of the material storage and distribution vehicle includes a charging and discharging energy behavior model of an electric material storage and distribution vehicle and a charging and discharging energy behavior model of a hydrogen material storage and distribution vehicle;

[0052] The charging and discharging behavior model of the electric material storage and distribution vehicle is as follows:

[0053]

[0054]

[0055]

[0056]

[0057]

[0058] S min ≤S v，t，ω ≤S max

[0059]

[0060] Among them, S v，t，ω is the energy state of the v-th vehicle; and are the charging power and discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the total battery charge of the vth vehicle; is the maximum and minimum value of the charge and discharge power of the vth vehicle; S min and S max The minimum and maximum values allowed by the energy state are respectively; the charging and discharging start time of the material storage and distribution vehicle Charging and discharging end time Energy state at the beginning of charging and discharging Expected state of charge at the end of charging and discharging

[0061] The charging and discharging behavior model of the hydrogen energy material storage and distribution vehicle is as follows:

[0062]

[0063]

[0064]

[0065]

[0066]

[0067] S min ≤S v，t，ω ≤S max

[0068]

[0069] in, and are the hydrogen charging power and hydrogen discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the hydrogen energy capacity of the vth vehicle; The maximum and minimum values of the hydrogen charging and discharging power of the vth vehicle; the charging and discharging start time of the material storage and distribution vehicle Charging and discharging end time Energy state at the beginning of charging and discharging Expected state of charge at the end of charging and discharging

[0070] Furthermore, the charging and discharging behavior model of the electric material storage and distribution vehicle and the charging and discharging behavior model of the hydrogen material storage and distribution vehicle are transformed using a linearization method:

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] in, and are the linearized charging power and discharging power of the electric material storage and distribution vehicle respectively; and They are respectively the linearized hydrogen charging power and hydrogen discharging power of the hydrogen energy material storage and distribution vehicle.

[0084] Furthermore, the equipment operating conditions include the total charging and discharging power of electric material storage and distribution vehicles and the total charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park, as shown below:

[0085]

[0086]

[0087]

[0088]

[0089] in, and They are the total charging and discharging power of the electric material storage and distribution vehicles in the material storage and distribution park; and They are the total hydrogen charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park.

[0090] Furthermore, the energy balance constraints of the material storage and distribution park are:

[0091] in, and are the output of photovoltaic and wind power respectively; P t load and are conventional electric load and hydrogen load respectively; P t DA and are the day-ahead purchased electricity power and day-ahead purchased hydrogen volume respectively; and They are real-time electricity purchase power and real-time electricity sales power respectively; and They are real-time hydrogen purchase volume and real-time hydrogen sales volume respectively; and are the charging power and discharging power of the energy storage system respectively; P el，t，ω and P FC，t，ω are the input electrical power of the electrolyzer and the output electrical power of the fuel cell respectively; and are the charging power and discharging power of all electric material storage and distribution vehicles in the park respectively; P com，t，ω The electrical power consumed by the compressor; and are the mass of hydrogen stored in the hydrogen storage tank and the mass of hydrogen released from the hydrogen storage tank respectively; H el，t，ω and H FC，t，ω are the output hydrogen mass of the electrolyzer and the input hydrogen mass of the fuel cell, respectively; and They are respectively the hydrogen charging power and hydrogen discharging power of all hydrogen energy material storage and distribution vehicles in the park.

[0092] A multi-energy conversion-based economic dispatch system for a material storage and distribution park includes a data acquisition module for acquiring historical output data of wind power and photovoltaic renewable energy within the material storage and distribution park, conventional electricity load data, conventional hydrogen load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, market hydrogen price data, and an objective function of the material storage and distribution park;

[0093] The electric-hydrogen conversion equipment model building module is used to obtain the model and constraints of the electric-hydrogen conversion equipment;

[0094] The hydrogen storage tank and energy storage system model building module is used to obtain the model and constraints of the hydrogen storage tank and energy storage system;

[0095] The energy transaction constraint construction module of the material storage and distribution park is used to obtain the energy transaction constraints of the material storage and distribution park;

[0096] Renewable energy typical scenario module, used to obtain typical renewable energy output scenarios and their occurrence probabilities based on historical data;

[0097] A module for constructing charging and discharging models for material storage and distribution vehicles, used to construct charging and discharging behavior models for electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles;

[0098] The energy balance constraint construction module of the material storage and distribution park is used to construct various energy balance constraints within the material storage and distribution park;

[0099] A material storage and distribution park economic dispatch optimization model construction module is used to construct an economic dispatch optimization model for the material storage and distribution park based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints, the typical renewable energy output scenario, the material storage and distribution vehicle charging and discharging behavior model, and the energy balance constraints of the material storage and distribution park;

[0100] The model solving module is used to solve the constructed economic scheduling optimization model of the material storage and distribution park to obtain the optimal economic scheduling solution.

[0101] The advantages and positive effects of the present invention are:

[0102] The present invention takes minimizing the economic cost of the material storage and distribution park as the objective function, and combines the electric-hydrogen conversion equipment model, hydrogen storage tank and energy storage system model, energy trading constraints, typical scenarios of renewable energy output, material storage and distribution vehicle charging and discharging behavior model, and material storage and distribution park energy balance constraints to establish an optimization scheduling model, and solves it to obtain the optimal economic scheduling plan, thereby effectively reducing the operating costs of the material storage and distribution park. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 A flow chart of an economic dispatching method for a material storage and distribution park based on multi-energy conversion in an embodiment provided by the present invention;

[0104] Figure 2 This is a schematic diagram of an economic dispatching system for a material storage and distribution park based on multi-energy conversion in an embodiment provided by the present invention. DETAILED DESCRIPTION

[0105] The present invention will be further described in detail below with reference to the accompanying drawings and through specific embodiments. The following embodiments are merely illustrative and non-restrictive, and the scope of protection of the present invention cannot be limited thereto.

[0106] Figure 1 The present invention provides a flow chart of a material storage and distribution park economic dispatch method based on multi-energy conversion, such as Figure 1 As shown, the present invention provides an economic dispatch method for a material storage and distribution park based on multi-energy conversion, comprising:

[0107] Step 100: Obtain relevant data.

[0108] Obtain historical output data of wind power and photovoltaic renewable energy within the material storage and distribution park, conventional electricity load data, conventional hydrogen load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, and market hydrogen price data;

[0109] And the economic dispatch objective function of the material storage and distribution park is constructed with the goal of obtaining the minimum economic cost;

[0110] Specifically, the economic scheduling objective function of the material storage and distribution park is:

[0111]

[0112] Where: T is all time periods in the scheduling period, the subscript t of each variable represents the value of the variable in time period t; Nsce is the number of typical scenarios, and the subscript ω represents the value of the variable in scenario ω; They are the day-ahead electricity purchase price, the real-time electricity purchase price and the real-time electricity sales price; They are the day-ahead hydrogen purchase price, real-time hydrogen purchase price and real-time hydrogen sales price; They are day-ahead electricity purchase power, real-time electricity purchase power, real-time electricity sales power, day-ahead hydrogen purchase volume, real-time hydrogen purchase volume, and real-time hydrogen sales volume; ρ ω The objective function includes the day-ahead electricity purchase cost, real-time net electricity purchase and sales cost, day-ahead hydrogen purchase cost, and real-time net hydrogen purchase and sales cost of the material storage and distribution park.

[0113] Step 200: Establish an electric-hydrogen conversion device model.

[0114] Establishing an electric-hydrogen conversion device model according to the parameters of the electric-hydrogen conversion device;

[0115] The material storage and distribution park is equipped with two types of electricity-hydrogen conversion equipment: electrolyzers and fuel cells. They can perform multi-energy conversion between electricity and hydrogen, realizing a flexible operation mode of multi-energy complementation. The electricity-hydrogen conversion equipment model is:

[0116] H el，t，ω =η el P el，t，ω

[0117] P FC，t，ω =η FC H FC，t，ω

[0118] Among them, η el and η FC are the conversion rates of electrolyzer and fuel cell respectively; P el，t，ω and H el，t，ω are the electric power input to the electrolyzer and the hydrogen mass output; H FC，t，ω and P FC，t，ω are the mass of hydrogen input to the fuel cell and the electrical power output, respectively.

[0119] Preferably, the constraints of the electric-hydrogen conversion equipment model are:

[0120] P el，min ≤P el，t，ω ≤P el，max

[0121] H FC，min ≤H FC，t，ω ≤H FC，max

[0122] Among them, P el，max 、P el，min 、H FC，max 、H FC，min They are the maximum and minimum values of the input electric power of the electrolyzer and the maximum and minimum values of the hydrogen input of the fuel cell, respectively.

[0123] Step 300: Establish a hydrogen storage tank and energy storage system model;

[0124] Establish a hydrogen storage tank and energy storage system model based on the parameters of the hydrogen storage tank and its energy storage system;

[0125] The model formula is as follows:

[0126]

[0127] P com，min ≤P com，t，ω ≤P com，max

[0128]

[0129] S H，1，ω =S H，T，ω

[0130]

[0131]

[0132] S H，min ≤S H，t，ω ≤S H，max

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] Among them, P com，t，ω is the electric power of the compressor; R H 、、T in ,κ,η com and P out / P inare the specific heat capacity constant of hydrogen, the temperature of compressed hydrogen, the hydrogen isentropic index, the compressor efficiency and the compression ratio; P is the mass of hydrogen that needs to be stored in the hydrogen storage tank. com,max and P com，min is the maximum and minimum value of the compressor electric power; S H，t，ω is the mass of hydrogen stored in the hydrogen storage tank; The mass of hydrogen released from the hydrogen storage tank; A 0-1 variable that indicates the state of the hydrogen storage tank. When it is 1, it means that hydrogen is stored in the tank, and when it is 0, it means that hydrogen is taken out of the tank. and are the efficiency of storing and releasing hydrogen in the hydrogen storage tank respectively; are the upper and lower limits of the hydrogen mass that can be stored and released in the hydrogen storage tank in each period; S H，min and S H，max are the minimum and maximum values of the hydrogen quality in the hydrogen storage tank respectively; is the state of charge of the energy storage system; It is a 0-1 variable indicating the charge and discharge state. When it is 1, it indicates charging, and when it is 0, it indicates discharging. and are the charging and discharging power of the energy storage system respectively; and are the charging and discharging efficiency of the energy storage system; are the upper and lower limits of the charging and discharging power of the energy storage system respectively; and are the upper and lower limits of the state of charge of the energy storage system respectively.

[0139] Step 400: Establish energy trading constraints for material storage and distribution parks;

[0140] Establish energy trading constraints for material storage and distribution parks based on market electricity price data and market hydrogen price data;

[0141] To avoid energy shortages within distribution parks, preventing them from supplying all loads or energy surpluses that cannot be absorbed, distribution parks can interact with external energy markets through specific trading mechanisms to improve supply reliability and effectively reduce operating costs. Energy trading within distribution parks can be categorized as day-ahead market trading and real-time market trading. Distribution parks sign energy purchase contracts in the day-ahead market, predetermining the amount to be purchased for each time period. During actual operation, energy is purchased or sold through the real-time market, thereby addressing the uncertainties of wind and solar power and maintaining power balance across time periods.

[0142] The energy trading constraints of the material storage and distribution park are:

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149] in, and are 0-1 variables representing the real-time purchase and sale status of electricity and hydrogen respectively, where 1 indicates purchase of the corresponding energy and 0 indicates sale of the corresponding energy; They are the upper and lower limits of the day-ahead electricity purchase and day-ahead hydrogen purchase, respectively; They are respectively the maximum and minimum values of real-time electricity purchase power, the maximum and minimum values of real-time electricity sales power, the maximum and minimum values of real-time hydrogen purchase volume, and the maximum and minimum values of real-time hydrogen sales volume.

[0150] Step 500: Obtain a typical output scenario of renewable energy.

[0151] Because the randomness and uncertainty of renewable energy output impact the economic costs of operating a distribution park, distribution park operators must fully consider the relative probability distributions of wind and solar output when formulating operational strategies. Using a large number of discrete probability distributions to represent the uncertainty of random variables is known as scenario simulation. It is called a scene ω, and the probability of the scene occurring is ρ ω , and has wind and solar output curves that are different from other scenarios. However, in order to reduce the computational burden and improve optimization efficiency, it is necessary to use a certain scene reduction method to reduce the large number of original scenes to a small number of representative typical scenes. The present invention uses the K-means clustering scene reduction method, and its specific steps are as follows:

[0152] 1) Randomly select Nsce cluster centers;

[0153] 2) Calculate the Euclidean distance from each remaining scene to each cluster center;

[0154] 3) Classify each remaining scene into the cluster center with the closest Euclidean distance to it;

[0155] 4) Re-determine the cluster center of each type of scene, calculate the sum of the Euclidean distances between each scene and other scenes of the same type, and select the scene with the smallest sum of the distances as the new cluster center of the scene type;

[0156] 5) Repeat steps 2) to 4) until the cluster center and clustering results no longer change.

[0157] 6) Output the clustering results. Each cluster center is the typical scene after reduction, and the probability of each typical scene is the sum of the probabilities of all scenes in the class.

[0158] Through this scenario reduction method, the output curves of typical photovoltaic and wind power scenarios and the corresponding scenario probabilities can be obtained.

[0159] Step 600: Establishing a charging and discharging behavior model for a material storage and distribution vehicle;

[0160] Considering that the material storage and distribution vehicles in the material storage and distribution park have their own material storage and distribution tasks, the establishment of the material storage and distribution vehicle charging and discharging behavior model requires obtaining the charging and discharging start time of each material storage and distribution vehicle according to its specific material storage and distribution task allocation. Charging and discharging end time Energy state at the beginning of charging and discharging Expected state of charge at the end of charging and discharging The charging and discharging model of the electric material storage and distribution vehicle is as follows:

[0161]

[0162]

[0163]

[0164]

[0165]

[0166] S min ≤S v，t，ω ≤S max

[0167]

[0168] Among them, S v，t，ω is the energy state of the v-th vehicle; and are the charging power and discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the total battery charge of the vth vehicle; is the maximum and minimum value of the charge and discharge power of the vth vehicle; S min and S maxare the minimum and maximum values allowed by the energy state, respectively.

[0169] The hydrogen charging and discharging model of the hydrogen energy material storage and distribution vehicle is as follows:

[0170]

[0171]

[0172]

[0173]

[0174]

[0175] S min ≤S v，t，ω ≤S max

[0176]

[0177] in, and are the hydrogen charging power and hydrogen discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the hydrogen energy capacity of the vth vehicle; are the maximum and minimum values of the hydrogen charging and discharging power of the vth vehicle.

[0178] The charging and discharging energy models of the electric material storage and distribution vehicle and the hydrogen material storage and distribution vehicle are transformed using a linearization method:

[0179]

[0180]

[0181]

[0182]

[0183]

[0184]

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191] The total charging and discharging power of electric material storage and distribution vehicles and the total charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park are as follows:

[0192]

[0193]

[0194]

[0195]

[0196] in, and They are the total charging and discharging power of the electric material storage and distribution vehicles in the material storage and distribution park; and They are the total hydrogen charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park.

[0197] Step 700: Establish various energy balance constraints for the material storage and distribution park:

[0198]

[0199]

[0200] in, and are the output of photovoltaic power and wind power respectively; are the conventional electricity load and hydrogen load respectively; P r DA and are the day-ahead purchased electricity power and day-ahead purchased hydrogen volume respectively; and They are real-time electricity purchase power and real-time electricity sales power respectively; and They are real-time hydrogen purchase volume and real-time hydrogen sales volume respectively; and are the charging power and discharging power of the energy storage system respectively; P el，t，ω and P FC，t，ω are the input electrical power of the electrolyzer and the output electrical power of the fuel cell respectively; and are the charging power and discharging power of all electric material storage and distribution vehicles in the park respectively; P com，t，ω The electrical power consumed by the compressor; and are the mass of hydrogen stored in the hydrogen storage tank and the mass of hydrogen released from the hydrogen storage tank respectively; H el，t，ω and H FC，t，ω are the output hydrogen mass of the electrolyzer and the input hydrogen mass of the fuel cell, respectively; and They are respectively the hydrogen charging power and hydrogen discharging power of all hydrogen energy material storage and distribution vehicles in the park.

[0201] Step 800: Construct an economic dispatch optimization model for the material storage and distribution park based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints, the typical renewable energy output scenario, the charging and discharging behavior model of the material storage and distribution vehicle, and the energy balance constraints of the material storage and distribution park.

[0202] Step 900: Call the Gurobi toolbox to solve the above optimization model to obtain the optimal operating conditions and optimal trading strategies of each equipment in the material storage and distribution park.

[0203] The present invention optimizes the charging and discharging scheduling of electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles based on the market price signals of various energy sources, combined with the demand of various loads in the material storage and distribution park, and considering the charging demand of material storage and distribution vehicles affected by material storage and distribution tasks. It also rationally plans the operation of various energy equipment in the material storage and distribution park, and proposes the optimal energy trading strategy, thereby achieving the optimal operating cost of the material storage and distribution park.

[0204] See also Figure 2 The present invention also provides a material storage and distribution park economic dispatching system based on multi-energy conversion, comprising:

[0205] The data acquisition module is used to obtain historical output data of renewable energy sources such as wind power and photovoltaic power within the material storage and distribution park, conventional electricity load data, conventional hydrogen load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, market hydrogen price data, and the objective function of the material storage and distribution park;

[0206] The electricity-to-hydrogen conversion equipment model building module is used to obtain the model and constraints of the electricity-to-hydrogen conversion equipment;

[0207] The hydrogen storage tank and energy storage system model building module is used to obtain the model and constraints of the hydrogen storage tank and energy storage system;

[0208] The energy transaction constraint construction module of the material storage and distribution park is used to obtain the energy transaction constraints of the material storage and distribution park;

[0209] Renewable energy typical scenario module, used to obtain typical renewable energy output scenarios and their occurrence probabilities based on historical data;

[0210] A module for constructing charging and discharging models for material storage and distribution vehicles, used to construct charging and discharging behavior models for electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles;

[0211] The energy balance constraint construction module of the material storage and distribution park is used to construct various energy balance constraints within the material storage and distribution park;

[0212] A material storage and distribution park economic dispatch optimization model construction module is used to construct an economic dispatch optimization model for the material storage and distribution park based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints, the typical renewable energy output scenario, the material storage and distribution vehicle charging and discharging behavior model, and the energy balance constraints of the material storage and distribution park;

[0213] The model solving module is used to solve the constructed economic scheduling optimization model of the material storage and distribution park to obtain the optimal economic scheduling solution.

[0214] The present invention optimizes the charging and discharging scheduling of electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles based on the market price signals of various energy sources, combined with the demand of various loads in the material storage and distribution park, and considering the charging demand of material storage and distribution vehicles affected by material storage and distribution tasks. It also rationally plans the operation of various energy equipment in the material storage and distribution park, and proposes the optimal energy trading strategy, thereby achieving the optimal operating cost of the material storage and distribution park.

[0215] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the description of the similarities between the various embodiments. For the methods disclosed in the embodiments, since they correspond to the devices disclosed in the embodiments, the description is relatively simple, and the relevant details can be referred to the description of the devices.

[0216] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for economic dispatching of material storage and distribution parks based on multi-energy conversion, characterized by: include: Obtain historical output data of wind power and photovoltaic renewable energy within the material storage and distribution park, conventional load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, and market hydrogen price data; The economic dispatch objective function of the material storage and distribution park is constructed with the goal of obtaining the minimum economic cost; Establishing an electric-hydrogen conversion device model according to the parameters of the electric-hydrogen conversion device; Establish a hydrogen storage tank and energy storage system model based on the parameters of the hydrogen storage tank and its energy storage system; Establishing energy transaction constraints for the material storage and distribution park based on the market electricity price data and the market hydrogen price data; Based on the historical output data of renewable energy sources such as wind power and photovoltaics, the scenario reduction method is used to obtain typical scenarios and corresponding probabilities of wind and solar output; Based on the charging and discharging energy requirements of electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles, a charging and discharging behavior model of material storage and distribution vehicles is established; Establish energy balance constraints for material storage and distribution parks based on energy transaction volume, equipment operating conditions, and conventional load data; An economic dispatch optimization model for the material storage and distribution park is constructed based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints of the material storage and distribution park, the typical wind and solar output scenarios, and the charging and discharging behavior model of the material storage and distribution vehicle. Solve the economic dispatch optimization model of the material storage and distribution park to obtain the optimal operating conditions of each device in the material storage and distribution park, the optimal trading strategies for the electricity and hydrogen markets, and the optimal charging and discharging strategies for material storage and distribution vehicles; The formula of the economic dispatch objective function of the resource storage and distribution park is: Where: T is all time periods in the scheduling period, the subscript t of each variable represents the value of the variable in time period t; Nsce is the number of typical scenarios, and the subscript ω represents the value of the variable in scenario ω; They are the day-ahead electricity purchase price, the real-time electricity purchase price and the real-time electricity sales price; are the day-ahead hydrogen purchase price, real-time hydrogen purchase price, and real-time hydrogen sales price respectively; P t DA 、 They are day-ahead electricity purchase power, real-time electricity purchase power, real-time electricity sales power, day-ahead hydrogen purchase volume, real-time hydrogen purchase volume, and real-time hydrogen sales volume; ρ ω is the probability of scenario ω occurring; the objective function includes the day-ahead electricity purchase cost, real-time net cost of electricity purchase and sale, day-ahead hydrogen purchase cost, and real-time net cost of hydrogen purchase and sale of the material storage and distribution park.

2. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 1 is characterized in that: The electricity-hydrogen conversion equipment includes two types: electrolyzers and fuel cells, both of which are installed in the material storage and distribution park. The electricity-hydrogen conversion equipment can perform multi-energy conversion of electricity and hydrogen energy, realizing a flexible operation mode of multi-energy complementation; and the electricity-hydrogen conversion equipment model is: H el，t,ω =the el P el，t,ω P FC,t,ω =the FC H FC,t,ω Among them, η el and η FC are the conversion rates of electrolyzer and fuel cell respectively; P el，t,ω and H el，t，ω are the electric power input to the electrolyzer and the hydrogen mass output; H FC，t，ω and P FC，t，ω are the hydrogen mass input to the fuel cell and the electrical power output; Constraints of the electric-to-hydrogen conversion equipment model: P el,min ≤P el,t，ω ≤P el,max H FC，min ≤H FC，t，ω ≤H FC,max Among them, P el,max 、P el，min 、H FC,max 、H FC,min They are the maximum input power of the electrolyzer, the minimum input power of the electrolyzer, the maximum hydrogen input of the fuel cell, and the minimum hydrogen input of the fuel cell.

3. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 1 is characterized in that: The hydrogen storage tank and energy storage system model is as follows: P com，min ≤P com，t，ω ≤P com,max S H，1，ω =S H，T，ω S H,min ≤S H，t，ω ≤S H,max Among them, P com，t，ω is the electric power of the compressor; R H 、T in ,κ,η com and P out / P in are the specific heat capacity constant of hydrogen, the temperature of compressed hydrogen, the hydrogen isentropic index, the compressor efficiency and the compression ratio; is the mass of hydrogen that needs to be stored in the hydrogen storage tank; P com，max and P com，min is the maximum value of the compressor electric power and the minimum value of the compressor electric power; S H,t，ω is the mass of hydrogen stored in the hydrogen storage tank; The mass of hydrogen released from the hydrogen storage tank; A 0-1 variable that indicates the state of the hydrogen storage tank. When it is 1, it means that hydrogen is stored in the tank, and when it is 0, it means that hydrogen is taken out of the tank. and are the efficiency of storing and releasing hydrogen in the hydrogen storage tank respectively; are the maximum and minimum values of the hydrogen mass that can be stored in the hydrogen storage tank in each period and the maximum and minimum values of the hydrogen mass that can be released; S H，min and S H，max are the minimum and maximum values of the hydrogen quality in the hydrogen storage tank respectively; is the state of charge of the energy storage system; It is a 0-1 variable indicating the charge and discharge state. When it is 1, it indicates charging, and when it is 0, it indicates discharging. and are the charging and discharging power of the energy storage system respectively; and are the charging and discharging efficiency of the energy storage system; They are the maximum value of charging power, the minimum value of charging power, the maximum value of discharging power, and the minimum value of discharging power respectively; and are the maximum and minimum state of charge of the energy storage system, respectively.

4. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 1 is characterized in that: The energy trading constraints of the material storage and distribution park are: in, and are 0-1 variables representing the real-time purchase and sale status of electricity and hydrogen respectively, where 1 indicates purchase of the corresponding energy and 0 indicates sale of the corresponding energy; They are the maximum and minimum values of electricity purchased the day before, the maximum and minimum values of hydrogen purchased the day before; They are respectively the maximum and minimum values of real-time electricity purchase power, the maximum and minimum values of real-time electricity sales power, the maximum and minimum values of real-time hydrogen purchase volume, and the maximum and minimum values of real-time hydrogen sales volume.

5. The economic dispatching method for material storage and distribution parks based on multi-energy conversion according to claim 1 is characterized in that: The charging and discharging energy requirements of the electric material storage and distribution vehicle are the same as those of the hydrogen material storage and distribution vehicle, and both include the charging and discharging start time of the material storage and distribution vehicle. Charging and discharging end time Expected state of charge at the end of charging and discharging The charging and discharging energy behavior model of the material storage and distribution vehicle includes a charging and discharging energy behavior model of an electric material storage and distribution vehicle and a charging and discharging energy behavior model of a hydrogen material storage and distribution vehicle; The charging and discharging behavior model of the electric material storage and distribution vehicle is as follows: S min ≤S v,t,ω ≤S max Among them, S v，t，ω is the energy state of the v-th vehicle; and are the charging power and discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the total battery charge of the vth vehicle; is the maximum and minimum value of the charge and discharge power of the vth vehicle; S min and S max The minimum and maximum values allowed by the energy state are respectively; the charging and discharging start time of the material storage and distribution vehicle Charging and discharging end time Expected state of charge at the end of charging and discharging The charging and discharging behavior model of the hydrogen energy material storage and distribution vehicle is as follows: S min ≤S v，t,ω ≤S max in, and are the hydrogen charging power and hydrogen discharging power of the vth vehicle respectively; and are the charging efficiency and discharging efficiency of the vth vehicle respectively; and are the charging and discharging decision variables of the vth vehicle respectively; is the hydrogen energy capacity of the vth vehicle; The maximum and minimum values of the hydrogen charging and discharging power of the vth vehicle; the charging and discharging start time of the material storage and distribution vehicle Charging and discharging end time Expected state of charge at the end of charging and discharging 6. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 5 is characterized by: The charging and discharging behavior model of the electric material storage and distribution vehicle and the charging and discharging behavior model of the hydrogen material storage and distribution vehicle are transformed using a linearization method: in, and are the linearized charging power and discharging power of the electric material storage and distribution vehicle respectively; and They are respectively the linearized hydrogen charging power and hydrogen discharging power of the hydrogen energy material storage and distribution vehicle.

7. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 1 is characterized in that: The equipment operating conditions include the total charging and discharging power of electric material storage and distribution vehicles and the total charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park, as shown below: in, and They are the total charging and discharging power of the electric material storage and distribution vehicles in the material storage and distribution park; and They are the total hydrogen charging and discharging power of hydrogen energy material storage and distribution vehicles in the material storage and distribution park.

8. The economic dispatching method for a material storage and distribution park based on multi-energy conversion according to claim 1 is characterized in that: Energy balance constraints of the material storage and distribution park: in, and are the output of photovoltaic and wind power respectively; P t load and are conventional electric load and hydrogen load respectively; P t DA and are the day-ahead purchased electricity power and day-ahead purchased hydrogen volume respectively; and They are real-time electricity purchase power and real-time electricity sales power respectively; and They are real-time hydrogen purchase volume and real-time hydrogen sales volume respectively; and are the charging power and discharging power of the energy storage system respectively; P el，t，ω and P FC，t，ω are the input electrical power of the electrolyzer and the output electrical power of the fuel cell respectively; and are the charging power and discharging power of all electric material storage and distribution vehicles in the park respectively; P com，t，ω The electrical power consumed by the compressor; and are the mass of hydrogen stored in the hydrogen storage tank and the mass of hydrogen released from the hydrogen storage tank respectively; H el，t，ω and H FC，t，ω are the output hydrogen mass of the electrolyzer and the input hydrogen mass of the fuel cell, respectively; and They are respectively the hydrogen charging power and hydrogen discharging power of all hydrogen energy material storage and distribution vehicles in the park.

9. A material storage and distribution park economic dispatching system based on multi-energy conversion, characterized by: It includes a data acquisition module for obtaining historical output data of wind power and photovoltaic renewable energy within the material storage and distribution park, conventional electricity load data, conventional hydrogen load data, charging and discharging requirements of electric material storage and distribution vehicles, charging and discharging requirements of hydrogen energy material storage and distribution vehicles, market electricity price data, market hydrogen price data, and the objective function of the material storage and distribution park; The electric-hydrogen conversion equipment model building module is used to obtain the model and constraints of the electric-hydrogen conversion equipment; The hydrogen storage tank and energy storage system model building module is used to obtain the model and constraints of the hydrogen storage tank and energy storage system; The energy transaction constraint construction module of the material storage and distribution park is used to obtain the energy transaction constraints of the material storage and distribution park; Renewable energy typical scenario module, used to obtain typical renewable energy output scenarios and their occurrence probabilities based on historical data; A module for constructing charging and discharging models for material storage and distribution vehicles, used to construct charging and discharging behavior models for electric material storage and distribution vehicles and hydrogen material storage and distribution vehicles; The energy balance constraint construction module of the material storage and distribution park is used to construct various energy balance constraints within the material storage and distribution park; A material storage and distribution park economic dispatch optimization model construction module is used to construct an economic dispatch optimization model for the material storage and distribution park based on the economic dispatch objective function of the material storage and distribution park, the electric-hydrogen conversion equipment model, the hydrogen storage tank and energy storage system model, the energy trading constraints, the typical renewable energy output scenario, the material storage and distribution vehicle charging and discharging behavior model, and the energy balance constraints of the material storage and distribution park; The model solving module is used to solve the constructed economic dispatch optimization model of the material storage and distribution park to obtain the optimal economic dispatch solution; The formula of the economic dispatch objective function of the resource storage and distribution park is: Where: T is all time periods in the scheduling period, the subscript t of each variable represents the value of the variable in time period t; Nsce is the number of typical scenarios, and the subscript ω represents the value of the variable in scenario ω; They are the day-ahead electricity purchase price, the real-time electricity purchase price and the real-time electricity sales price; are the day-ahead hydrogen purchase price, real-time hydrogen purchase price, and real-time hydrogen sales price respectively; P t DA 、 They are day-ahead electricity purchase power, real-time electricity purchase power, real-time electricity sales power, day-ahead hydrogen purchase volume, real-time hydrogen purchase volume, and real-time hydrogen sales volume; ρ ω is the probability of scenario ω occurring; the objective function includes the day-ahead electricity purchase cost, real-time net cost of electricity purchase and sale, day-ahead hydrogen purchase cost, and real-time net cost of hydrogen purchase and sale of the material storage and distribution park.

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