Intelligent operation and maintenance platform for smart energy rail transit system

Abstract

The invention provides an intelligent operation and maintenance platform for a smart energy rail transit system, which belongs to the field of urban energy smart operation management and comprises an energy supply side database module, an energy type matching module, a model establishment module and a management module. According to the invention, through the arrangement of the energy supply side database module, the energy type matching module, the model establishment module and the management module, renewable energy during subway braking can be collected and used, and renewable energy along the subway and around the subway can be dispatched; the developed intelligent operation management platform of the subway system center can monitor and adjust the energy supply side and the demand side in real time so as to realize efficient matching with the energy consumption of the subway station.

Description

Technical Field

[0001] The present invention belongs to the field of smart operation and management of urban energy, and specifically relates to an intelligent operation and maintenance platform for a smart energy rail transit system. Background Art

[0002] The notable feature of the integrated energy system is its multi-energy interconnectedness. The system breaks the traditional model of independent and unrelated energy systems and realizes the organic coordination and comprehensive utilization of various energy sources. Through multi-energy coupling, various forms of energy are concentratedly utilized to promote the interaction, mutual coordination and complementary advantages between energy supply and demand, significantly improve the efficiency of energy utilization, and promote the transition from traditional energy to cleaner energy, bringing low-carbon benefits, ecological benefits and economic benefits. At present, the integrated energy system is mainly used in various factories and parks, such as industrial parks, ecological parks, etc., while the application of subway stations is relatively small.

[0003] As an important part of urban public transportation, the subway system's energy consumption is increasing, and the demand for energy is also increasing. With the continuous development of the national economy and the acceleration of urbanization, the subway has become one of the main forms of urban public transportation, and the speed of construction and expansion has increased rapidly. According to the "Statistical and Analysis Report on Urban Rail Transit in 2023" released by the China Urban Rail Transit Association, the total power consumption of urban rail transit in China in 2023 will be 24.977 billion kWh, of which traction power consumption will reach 12.934 billion kWh, accounting for 51.97% of the total power consumption. At the same time, subway stations need to withstand high load operation during peak hours, resulting in uneven energy utilization efficiency and huge energy waste.

[0004] The existing smart operation and management platform based on subway stations focuses on the intelligent prediction and allocation of energy demand. The platform integrates emerging technologies such as big data, AI, IoT, video, GIS, BIM, etc. Based on the urban rail cloud platform, it integrates the business and data of stations, lines, networks and terminals, realizes the intelligent operation and comprehensive management of stations, and provides highly integrated smart monitoring services for the station's energy system. However, these smart energy systems mainly focus on the management of electricity consumption. They install smart meters to collect and monitor the electricity consumption of station elevators, lighting, environmental control and other equipment in real time, and rely on cloud platform services to monitor and analyze equipment energy consumption. By comparing with the energy consumption data of a specific historical period, analyzing the energy consumption trend, and combining application scenarios and energy-saving strategies to formulate a reasonable equipment control plan, energy saving and consumption reduction can be achieved.

[0005] At the same time, the existing subway smart operation and management platform ignores the energy supply side, especially the evaluation of the comprehensive utilization potential of renewable energy along the line. Since there is a significant temporal unevenness in the energy consumption of subway stations, that is, there is a significant difference in energy demand between peak and off-peak periods, this leads to an urgent need to solve the energy allocation problem and brings new challenges to the design and operation of energy storage systems. These systems need to adapt to the temporal and spatial demand characteristics of rail transit energy. Summary of the invention

[0006] In view of this, the present invention provides an intelligent operation and maintenance platform for a smart energy rail transit system, which can collect and use renewable energy during subway braking, dispatch renewable energy along the subway line and surrounding areas, and recover waste heat. The developed smart operation and management platform of the subway system center can monitor and adjust the energy supply and demand sides in real time to achieve efficient matching with the energy consumption of subway stations.

[0007] The technical solution adopted by the present invention is as follows:

[0008] An intelligent operation and maintenance platform for a smart energy rail transit system, comprising:

[0009] (1) Energy supply side database module: The energy supply side database model includes a variety of renewable energy sources available along the subway line;

[0010] The renewable energy sources include regenerative braking energy, solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat, and the regenerative braking energy is used for station load.

[0011] For solar energy, we can make full use of the station entrance and exit roofs and open-air areas of the vehicle depot to collect sunlight resources, and set up photovoltaic power generation modules in these areas to reduce the demand for electricity from the grid; set up wind turbines in areas with a breeze speed of about 3m / s (such as plain areas with wind speeds that meet the standards), and even consider using the piston wind effect of the tunnel to generate electricity using tunnel wind energy.

[0012] (2) Energy type matching module: The energy type matching module obtains energy types that match the energy types required by the energy demand side in the energy supply side database model based on the energy types required by the energy demand side in the time sequence;

[0013] (Since the frequency and time of subway vehicle departures are closely related to passenger flow, and passenger flow is related to the surrounding environment of the subway station (surrounding building types, whether it is a transfer station, whether it is a transportation hub, etc.), and the working hours of the subway work area and surrounding businesses are different, the resulting uneven temporal and spatial distribution requires that energy types that can match this feature should be obtained in the pre-created energy supply-side database).

[0014] (3) Model building module: for each type of renewable energy and the influencing parameters affecting the output of renewable energy, establish an energy mathematical model for each renewable energy; integrate the energy mathematical models of each renewable energy to obtain a demand-side energy mathematical model;

[0015] (3.1) For each type of renewable energy and the influencing parameters affecting the output of renewable energy, an energy mathematical model for each renewable energy is established, including:

[0016] Mathematical models of solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat are established respectively.

[0017] (3.11) The solar energy mathematical model is established by the following steps:

[0018] Step A1: Get the total area of ​​solar panels;

[0019] Step A2: Obtaining the conversion efficiency of the solar panel;

[0020] Step A3: Obtain solar radiation intensity in real time;

[0021] Step A4: A solar energy mathematical model is established based on the data obtained from steps A1 to A4, as shown in the following formula:

[0022] E pv =F(A pv ,η,G,t)=A pv *η*G*t;

[0023] In the formula, A pv Represents the area of ​​the solar panel (m 2 ), η represents the conversion efficiency of the solar panel, G represents the solar radiation intensity (W / m 2 ), t represents the solar radiation time (h).

[0024] (3.12) The calculation formula of wind energy is usually estimated based on the kinetic energy of wind. Wind energy can be expressed as the work done by the force of wind acting on the wind rotor blades. The calculation formula is as follows:

[0025] E w =f(ρ,A w , V, Cp) = 0.5*ρ*Aw*V^3*Cp

[0026] Where ρ represents the air density (kg / m 3 ), A w Represents the effective area of ​​the wind rotor blades (m 2), V represents the wind speed (m / s), and Cp represents the power coefficient of the wind energy conversion system (usually between 0.3 and 0.45).

[0027] (3.13) The calculation formula of biomass energy can be estimated by the heat generated by biomass combustion or fermentation. The calorific value of biomass energy is usually used to express the energy released by the combustion of unit mass of biomass. The calculation formula is as follows:

[0028] E b =f(m b , H)=m b *H

[0029] In the formula, m b represents the mass of biomass (kg), and H represents the calorific value of biomass (in J / kg or kJ / kg).

[0030] (3.14) Hydrogen energy has been widely studied and explored in the energy field. The main source is the production of hydrogen through the electrolysis of water. The energy of hydrogen can be calculated by the following formula:

[0031] E H =f(P, t) = P*t

[0032] In the formula, P represents the power of hydrogen production by electrolysis (W or kW), and t represents the time of hydrogen production by electrolysis (h).

[0033] (3.15) The calculation of geothermal energy usually involves the reserves and temperature of geothermal resources. The theoretical output of geothermal energy can be estimated by the following formula:

[0034] E g =f(m g , C, ΔT) = m g *C*ΔT

[0035] In the formula, m g represents the mass of geothermal water or steam (kg), C represents the specific heat capacity of water or steam (J / kg·℃), and ΔT represents the temperature change of water or steam (℃).

[0036] (3.16) Industrial waste heat refers to the heat generated during industrial production. If this heat can be effectively recovered and utilized, energy conservation and environmental protection can be achieved. The calculation of industrial waste heat can be estimated using the following formula:

[0037] E i =f(m i , Cp, ΔT) = m i *Cp*ΔT

[0038] In the formula, m iIt represents the mass (kg) of the substance that generates waste heat in the industrial production process, Cp represents the specific heat capacity of the substance (J / kg·℃), and ΔT represents the temperature change (℃).

[0039] (3.17) Nuclear energy refers to the energy released in nuclear reactions, usually through nuclear fission or nuclear fusion. Nuclear energy can be estimated using the mass-energy equivalence principle, where the energy released by nuclear reactions can be calculated using the following formula:

[0040] E n =f(m n , c) = m n *c^2

[0041] In the formula, m n represents the mass of the nuclear reaction (kg), and c represents the speed of light (approximately 3×10^8m / s).

[0042] The energy supply side consists of solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy, industrial waste heat, microgrids, national grids, and natural gas pipelines. It considers the simultaneous operation of multiple energy sources such as transportation, water, heat, electricity, and cooling energy to achieve the optimal solution for integration. The integration of the energy system with the subway coordination center is called the smart energy rail transit system, which includes microgrids, national grids, energy hubs, and smart transportation systems. Through the system's multi-source optimization and scheduling, the water, heat, electricity, and cooling needs of the subway can be met, thereby reducing the operating costs of smart cities.

[0043] As the energy demand side of the synchronous operation of multiple energy sources, the subway system can be divided into functional areas according to different functions: platform, station hall, train, and ancillary buildings. The energy composition of the subway system is divided into the following categories: subway system lighting, ventilation and air conditioning electricity, train traction electricity, surrounding supporting facilities electricity, subway system equipment electricity, and subway station surrounding building load electricity. Among them, train traction electricity and ventilation and air conditioning electricity account for the largest proportion.

[0044] (3.18) The mathematical model of demand-side energy is:

[0045] Q sum =Q l +Q ac +Q t +Q a +Q s

[0046] In the formula, Q sum Total energy on the demand side, Q l represents the lighting power consumption of the subway system, Q ac Indicates the electricity used for ventilation and air conditioning, Q t Indicates the train traction power, Q aIndicates the electricity consumption of supporting facilities of the subway system, Q s Indicates the electricity consumption of building loads around the subway station.

[0047] As a preference, the mathematical model on the energy demand side should include sub-item mathematical models for each specific energy type (some mathematical models only describe the proportional relationship with the influencing factors), including:

[0048] (3.19)S4.2.1: The lighting power consumption of the subway system is mainly affected by the number of lighting equipment and the power of the lighting equipment. Therefore, the mathematical model of the subway system lighting is:

[0049] Q l =f(n l , P l )=n l *P l

[0050] Where n l Indicates the number of lighting equipment, P l Indicates the power of the lighting device.

[0051] (3.20) The electricity consumption of ventilation and air conditioning is mainly affected by the number of passengers, the length of stay, outdoor meteorological parameters and the frequency of train arrival, so the mathematical model is:

[0052] Q ac ∝n p , τ p , t o , f t

[0053] Where n p represents the number of passenger flows, τ p represents the passenger flow residence time, t o represents outdoor meteorological parameters, f t Indicates the frequency of train arrival.

[0054] (3.21) The power consumption of train traction is mainly affected by the technical speed, ambient temperature, traffic frequency and passenger flow of each section, so the mathematical model is:

[0055] Q t ∝v t , t e ,φ t , n p

[0056] In the formula, v t represents the technical speed of each interval, t e represents the ambient temperature of each interval, φ t Indicates the traffic frequency, n p Indicates the passenger flow size in each section.

[0057] (3.22) The electricity consumption of supporting facilities in the subway system is mainly affected by the number of facilities and the power size, so the mathematical model is:

[0058] Q a =f(n a , P a )=n a *P a

[0059] Where n a represents the number of facilities, P a Indicates the power size of the facility.

[0060] (3.23) The power consumption of surrounding building loads is mainly affected by passenger flow, so the mathematical model is:

[0061] Q s ∝n p

[0062] Where, T t Indicates the type of subway station, n p Indicates the size of passenger flow.

[0063] (4) Management module: obtains the output of each renewable energy source in the model building module, and dispatches the energy from the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series;

[0064] The management module comprises:

[0065] (4.1) Monitoring module: The monitoring module monitors the energy storage capacity of the energy acquisition and storage module and the energy consumption of the energy demand side in real time;

[0066] (4.2) Energy storage module: when the energy supply on the supply side is greater than the energy demand on the demand side, the energy storage module stores the excess energy;

[0067] (4.3) Energy dispatch module: dispatches energy from the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series;

[0068] (4.4) When the energy demand on the energy demand side is greater than the energy provided on the supply side, the energy scheduling module schedules the energy of the energy storage module to the energy demand side.

[0069] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0070] 1. In the present invention, by making full use of the means of smart energy operation and management, the energy supply and demand sides of the subway system can be balanced, providing method support for formulating targeted energy-saving plans;

[0071] 2. In the present invention, it is possible to collect and use renewable energy during subway braking, dispatch renewable energy along the subway line and surrounding areas, and recover waste heat. The intelligent operation and management platform of the subway system center developed can monitor and adjust the energy supply and demand sides in real time to achieve efficient matching with the energy consumption of subway stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The present invention will now be described by way of example with reference to the accompanying drawings, in which:

[0073] Figure 1 It is a structural schematic diagram of the intelligent operation and maintenance platform of the present invention.

[0074] Figure 2 It is a schematic diagram of the structure between various modules of the present invention. DETAILED DESCRIPTION

[0075] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0076] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0077] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0078] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0079] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0080] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0081] Example

[0082] like Figure 1 and Figure 2 In an embodiment of the present invention, an intelligent operation and maintenance platform for a smart energy rail transit system is disclosed, comprising:

[0083] (1) Energy supply side database module: The energy supply side database model includes a variety of renewable energy sources available along the subway line;

[0084] The renewable energy sources include regenerative braking energy, solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat, and the regenerative braking energy is used for station load.

[0085] For solar energy, we can make full use of the station entrance and exit roofs and open-air areas of the vehicle depot to collect sunlight resources, and set up photovoltaic power generation modules in these areas to reduce the demand for electricity from the grid; set up wind turbines in areas with a breeze speed of about 3m / s (such as plain areas with wind speeds that meet the standards), and even consider using the piston wind effect of the tunnel to generate electricity using tunnel wind energy.

[0086] (2) Energy type matching module: The energy type matching module obtains energy types that match the energy types required by the energy demand side in the energy supply side database model based on the energy types required by the energy demand side in the time sequence;

[0087] (Since the frequency and time of subway vehicle departures are closely related to passenger flow, and passenger flow is related to the surrounding environment of the subway station (surrounding building types, whether it is a transfer station, whether it is a transportation hub, etc.), and the working hours of the subway work area and surrounding businesses are different, the resulting uneven temporal and spatial distribution requires that energy types that can match this feature should be obtained in the pre-created energy supply-side database).

[0088] (3) Model building module: for each type of renewable energy and the influencing parameters affecting the output of renewable energy, establish an energy mathematical model for each renewable energy; integrate the energy mathematical models of each renewable energy to obtain a demand-side energy mathematical model;

[0089] (3.1) For each type of renewable energy and the influencing parameters affecting the output of renewable energy, an energy mathematical model for each renewable energy is established, including:

[0090] Mathematical models of solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat are established respectively.

[0091] (3.11) The solar energy mathematical model is established by the following steps:

[0092] Step A1: Get the total area of ​​solar panels;

[0093] Step A2: Obtaining the conversion efficiency of the solar panel;

[0094] Step A3: Obtain solar radiation intensity in real time;

[0095] Step A4: A solar energy mathematical model is established based on the data obtained from steps A1 to A4, as shown in the following formula:

[0096] E pv =F(A pv ,η,G,t)=A pv *η*G*t;

[0097] In the formula, A pv Represents the area of ​​the solar panel (m 2 ), η represents the conversion efficiency of the solar panel, G represents the solar radiation intensity (W / m 2 ). t represents the solar radiation time (h).

[0098] (3.12) The calculation formula of wind energy is usually estimated based on the kinetic energy of wind. Wind energy can be expressed as the work done by the force of wind acting on the wind rotor blades. The calculation formula is as follows:

[0099] E w =f(ρ,A w , V, Cp) = 0.5ρ*Aw*V^3*Cp

[0100] Where ρ represents the air density (kg / m 3 ), A w Represents the effective area of ​​the wind rotor blades (m 2), V represents the wind speed (m / s), and Cp represents the power coefficient of the wind energy conversion system (usually between 0.3 and 0.45).

[0101] (3.13) The calculation formula of biomass energy can be estimated by the heat generated by biomass combustion or fermentation. The calorific value of biomass energy is usually used to express the energy released by the combustion of unit mass of biomass. The calculation formula is as follows:

[0102] E b =f(m b , H)=m b *H

[0103] In the formula, m b represents the mass of biomass (kg), and H represents the calorific value of biomass (in J / kg or kJ / kg).

[0104] (3.14) Hydrogen energy has been widely studied and explored in the energy field. The main source is the production of hydrogen through the electrolysis of water. The energy of hydrogen can be calculated by the following formula:

[0105] E H =f(P, t) = P*t

[0106] In the formula, P represents the power of hydrogen production by electrolysis (W or kW), and t represents the time of hydrogen production by electrolysis (h).

[0107] (3.15) The calculation of geothermal energy usually involves the reserves and temperature of geothermal resources. The theoretical output of geothermal energy can be estimated by the following formula:

[0108] E g =f(m g , C, ΔT) = m g *C*ΔT

[0109] In the formula, m g represents the mass of geothermal water or steam (kg), C represents the specific heat capacity of water or steam (J / kg·℃), and ΔT represents the temperature change of water or steam (℃).

[0110] (3.16) Industrial waste heat refers to the heat generated during industrial production. If this heat can be effectively recovered and utilized, energy conservation and environmental protection can be achieved. The calculation of industrial waste heat can be estimated using the following formula:

[0111] E i =f(m i , Cp, ΔT) = m i *Cp*ΔT

[0112] In the formula, m iIt represents the mass (kg) of the substance that generates waste heat in the industrial production process, Cp represents the specific heat capacity of the substance (J / kg·℃), and ΔT represents the temperature change (℃).

[0113] (3.17) Nuclear energy refers to the energy released in nuclear reactions, usually through nuclear fission or nuclear fusion. Nuclear energy can be estimated using the mass-energy equivalence principle, where the energy released by nuclear reactions can be calculated using the following formula:

[0114] E n =f(m n , c) = m n *c^2

[0115] In the formula, m n represents the mass of the nuclear reaction (kg), and c represents the speed of light (approximately 3×10^8m / s).

[0116] The energy supply side consists of solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy, industrial waste heat, microgrids, national grids, and natural gas pipelines. It considers the simultaneous operation of multiple energy sources such as transportation, water, heat, electricity, and cooling energy to achieve the optimal solution for integration. The integration of the energy system with the subway coordination center is called the smart energy rail transit system, which includes microgrids, national grids, energy hubs, and smart transportation systems. Through the system's multi-source optimization and scheduling, the water, heat, electricity, and cooling needs of the subway can be met, thereby reducing the operating costs of smart cities.

[0117] As the energy demand side of the synchronous operation of multiple energy sources, the subway system can be divided into functional areas according to different functions: platform, station hall, train, and ancillary buildings. The energy composition of the subway system is divided into the following categories: subway system lighting, ventilation and air conditioning electricity, train traction electricity, surrounding supporting facilities electricity, subway system equipment electricity, and subway station surrounding building load electricity. Among them, train traction electricity and ventilation and air conditioning electricity account for the largest proportion.

[0118] (3.18) The mathematical model of demand-side energy is:

[0119] Q sum =Q1+Q ac +Q t +Q a +Q s

[0120] In the formula, Q sum Total energy on the demand side, Q l represents the lighting power consumption of the subway system, Q ac Indicates the electricity used for ventilation and air conditioning, Q t Indicates the train traction power, Q a Indicates the electricity consumption of supporting facilities of the subway system, Q sIndicates the electricity consumption of building loads around the subway station.

[0121] As a preference, the mathematical model on the energy demand side should include sub-item mathematical models for each specific energy type (some mathematical models only describe the proportional relationship with the influencing factors), including:

[0122] (3.19) The lighting power consumption of the subway system is mainly affected by the number of lighting equipment and the power of the lighting equipment. Therefore, the mathematical model of the subway system lighting is:

[0123] Q l =f(n l , P l )=n l *P l

[0124] Where n l Indicates the number of lighting equipment, P l Indicates the power of the lighting device.

[0125] (3.20) The electricity consumption of ventilation and air conditioning is mainly affected by the number of passengers, the length of stay, outdoor meteorological parameters and the frequency of train arrival, so the mathematical model is:

[0126] Q ac ∝n p , τ p , t o , f t

[0127] Where n p represents the number of passenger flows, τ p represents the passenger flow residence time, t o represents outdoor meteorological parameters, f t Indicates the frequency of train arrival.

[0128] (3.21) The power consumption of train traction is mainly affected by the technical speed, ambient temperature, traffic frequency and passenger flow of each section, so the mathematical model is:

[0129] Q t ∝v t , t e ,φ t , n p

[0130] In the formula, v t represents the technical speed of each interval, t e represents the ambient temperature of each interval, φ t Indicates the traffic frequency, n p Indicates the passenger flow size in each section.

[0131] (3.22) The electricity consumption of supporting facilities in the subway system is mainly affected by the number of facilities and the power size, so the mathematical model is:

[0132] Q a =f(n a , P a )=n a *P a

[0133] Where n a represents the number of facilities, P a Indicates the power size of the facility.

[0134] (3.23) The power consumption of surrounding building loads is mainly affected by passenger flow, so the mathematical model is:

[0135] Q s ∝n p

[0136] Where, T t Indicates the type of subway station, n p Indicates the size of passenger flow.

[0137] (4) Management module: obtains the output of each renewable energy source in the model building module, and dispatches the energy from the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series;

[0138] The management module comprises:

[0139] (4.1) Monitoring module: The monitoring module monitors the energy storage capacity of the energy acquisition and storage module and the energy consumption of the energy demand side in real time;

[0140] (4.2) Energy storage module: When the energy supply on the supply side is greater than the energy demand on the demand side, the energy storage module stores the excess energy:

[0141] (4.3) Energy dispatch module: dispatches energy from the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series;

[0142] (4.4) When the energy demand on the energy demand side is greater than the energy provided on the supply side, the energy scheduling module schedules the energy of the energy storage module to the energy demand side.

[0143] This embodiment also provides a data management framework for smart operation management, including: 1. platform area sensors, 2. station hall area sensors, 3. train operation area sensors, 4. ancillary building area sensors; it also includes a data and energy management center, a private blockchain, a public blockchain and a transaction blockchain.

[0144] Specific:

[0145] In terms of temporal unevenness, there are differences in the supply of renewable energy on the supply side and the energy demand of each section of the subway system on the demand side. For example, solar energy is generally at its peak between 11 a.m. and 2 p.m., when the most solar energy is available. The peak energy consumption of the subway system is mainly related to changes in passenger flow, which is generally peak during the morning commute and evening get-off periods. This leads to a mismatch in time between the energy required near different platforms and the renewable energy we can generate.

[0146] In response to spatial unevenness, the renewable energy selected on the supply side is distributed near the subway network; on the demand side, the closer to the integrated transportation hub in the city center, the greater the energy consumption required, and the energy supply in the surrounding area is small. For example, some subway stations are sparsely populated, but there is abundant renewable energy available. For subway stations with large tracts of open space, abundant solar energy can be used. This leads to a spatial mismatch between the energy required near different platforms and the renewable energy we can generate.

[0147] In order to solve the problem of uneven temporal and spatial distribution, the energy consumption in different areas is fed back to the data and energy management center hour by hour through sensors in various sections of the subway system, and then automatic energy scheduling is realized through a visual interface. Finally, blockchain technology is used in the process of data interaction to ensure the security of energy exchange.

[0148] The circuits, electronic components and modules involved are all prior art and can be fully implemented by those skilled in the art. Needless to say, the content protected by the present invention does not involve improvements to software and methods.

[0149] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0150] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent operation and maintenance platform for a smart energy rail transit system, characterized in that: include: Energy supply side database module: the energy supply side database model includes a variety of renewable energy sources available along the subway line; Energy type matching module: the energy type matching module obtains energy types that match the energy types required by the energy demand side in the energy supply side database model based on the energy types required by the energy demand side in the time sequence; Model building module: for each type of renewable energy and the parameters affecting the output of renewable energy, establish the energy mathematical model of each renewable energy; Integrate the energy mathematical model of each of the renewable energy sources to obtain a demand-side energy mathematical model; Management module: obtains the output of each renewable energy in the model building module, and dispatches the energy of the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series.

2. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 1, characterized in that: The management module comprises: Monitoring module: The monitoring module monitors the energy storage capacity of the energy acquisition and storage module and the energy consumption of the energy demand side in real time; Energy storage module: when the energy supply on the supply side is greater than the energy demand on the demand side, the energy storage module stores the excess energy; Energy dispatch module: dispatches energy from the energy supply side database module to the energy demand side in real time according to the energy consumption data of each energy demand side in the time series; When the energy demand on the energy demand side is greater than the energy provided on the supply side, the energy scheduling module schedules the energy of the energy storage module to the energy demand side.

3. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 1, characterized in that: The renewable energy sources include regenerative braking energy, solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat, and the regenerative braking energy is used for station load.

4. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 1, characterized in that: The energy mathematical model of each renewable energy source is established for each type of renewable energy source and the influencing parameters affecting the output of renewable energy source, including: Mathematical models of solar energy, geothermal energy, biomass energy, hydrogen energy, nuclear energy, wind energy and industrial waste heat are established respectively.

5. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 4, characterized in that: The solar energy mathematical model is established by the following steps: Step A1: Get the total area of ​​solar panels; Step A2: Obtaining the conversion efficiency of the solar panel; Step A3: Obtain solar radiation intensity in real time; Step A4: A solar energy mathematical model is established based on the data obtained from steps A1 to A4, as shown in the following formula: E pv =f(A pv ,η,G,t)=A pv *η*G*t; In the formula, A pv represents the area of ​​the solar panel, η represents the conversion efficiency of the solar panel, G represents the solar radiation intensity, and t represents the solar radiation time.

6. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 4, characterized in that: The wind energy mathematical model is established by the following formula: E w =f(ρ,A w ,V,Cp)=0.5*ρ*Aw*V^3*Cp; Where ρ represents the air density, A w represents the effective area of ​​the wind rotor blades, V represents the wind speed, and Cp represents the power coefficient of the wind energy conversion system.

7. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 4, characterized in that: The biomass energy mathematical model is established by the following formula: E b =f(m b ,H)=m b *H In the formula, m b represents the mass of biomass, and H represents the calorific value of biomass.

8. The intelligent operation and maintenance platform for a smart energy rail transit system according to claim 4, characterized in that: The geothermal energy mathematical model is established by the following formula: E g =f(m g ,C,ΔT)=m g *C*ΔT In the formula, m g represents the mass of geothermal water or steam, C represents the specific heat capacity of water or steam, and ΔT represents the temperature change of water or steam.

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