Energy management strategy for accessing new energy to active traction substation

Abstract

The invention discloses an energy management strategy for access of new energy to an active traction substation, and the strategy comprises the steps: collecting historical new energy output and historical meteorological data of a target substation, historical traction load data and a driving working diagram, so as to obtain a new energy output prediction value and a traction load power prediction value of a specified time period; configuring preset charging and discharging thresholds matched with different degrees of traction load demands for the target substation, thereby judging the working state of the energy storage system in a specified time period in combination with each predicted value, and calculating the power of the energy storage system in the current working state; according to the predicted values and the calculated power, reactive power transferred by the interface and used for improving the power factor of the substation and active power transferred by the interface and used for reducing the negative-sequence current of the substation are obtained, the interface capacity is determined based on the reactive power and the active power, and the interface is an energy transmission channel from the energy storage system to the target substation. According to the invention, energy management and capacity configuration of the new energy access energy storage system are effectively realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrified railway energy management, and in particular relates to an energy management strategy for connecting new energy to an active traction substation. Background Art

[0002] The rapid development of electrified railways has led to an increase in carbon emissions and energy consumption. In order to achieve cost-saving and green development of railways, energy storage and renewable energy are usually connected to the traction power supply system at the same time. China Railway currently implements a two-part electricity price: one part is the electricity fee per kilowatt-hour, which is calculated based on actual electricity consumption; the other part is the basic electricity fee, which is charged according to the capacity of the transformer or the maximum load demand. Therefore, peak shaving can effectively reduce the expenditure of basic electricity fees and electricity fees per kilowatt-hour.

[0003] At present, the interface capacity configuration strategy and management of electrified railway energy storage mainly include: (1) Single energy storage uses a single fixed threshold peak-shaving and valley-filling interface capacity configuration strategy for capacity optimization, which cannot take into account the basic electricity fee and electricity fee benefits (the discharge threshold is too low, which cannot effectively reduce the maximum demand and cannot guarantee the basic electricity fee benefits; the discharge threshold is too high, the utilization rate of regenerative braking energy is low, and the electricity fee benefits cannot be guaranteed); (2) The energy storage medium mainly adopts a multi-threshold and allocation ratio interface capacity configuration strategy, which can take into account the requirements of railway load energy density and power density and obtain better economic benefits, but in actual applications, there are problems such as high initial investment cost, long payback period, and relatively complex control. In addition, the management of electrified railway new energy systems is mainly solved with the goal of maximizing net benefits. In actual engineering applications, there are also problems such as high initial investment cost and long investment payback period. Summary of the invention

[0004] In order to solve the above problems, an embodiment of the present invention provides an energy management strategy for accessing new energy to an active traction substation, including: collecting historical new energy output and historical meteorological data, historical traction load data and driving operation diagrams of the target substation to obtain new energy output forecast values ​​and traction load power forecast values ​​for a specified time period; configuring preset charging and discharging thresholds for the target substation that match different degrees of traction load demand, so as to determine the working state of the energy storage system in the specified time period in combination with each predicted value, and calculate the power of the energy storage system in the current working state; according to the predicted values ​​and the calculated power, the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation are obtained, and based on this, the interface capacity is determined, wherein the interface is the energy transmission channel from the energy storage system to the target substation.

[0005] Preferably, after determining the capacity of the interface, the energy management strategy also includes: taking net income, investment payback period and rate of return as objective functions, establishing a full life cycle economic model of the power supply system in which the energy storage system is located, so as to optimize the current interface capacity by solving the objective function, and obtain the corresponding optimal new energy installed capacity and optimal energy storage access capacity.

[0006] Preferably, the life cycle economic model is expressed using the following expression:

[0007]

[0008] Among them, F 1 represents net income, N represents the project period, T represents the year, and R T Indicates annual electricity savings, C om.T represents the annual operating cost, C con represents the initial investment cost, F 2 represents the payback period, T PP represents the payback period, F 3 Indicates the rate of return.

[0009] Preferably, the working state is determined in the order of the discharge state in the peak shaving working mode, the standby state in the standby working mode, the charging state in the new energy electric energy recovery mode and the charging state in the valley filling working mode, wherein the step of determining the working state of the energy storage system in the specified time period includes: if the difference between the traction load active power prediction value and the preset discharge threshold is greater than or equal to the new energy output prediction value, the determination result is the discharge state in the peak shaving working mode; if the new energy output prediction value is greater than the difference between the traction load active power prediction value and the preset discharge threshold, and is less than the traction load active power prediction value, the determination result is the standby state in the standby working mode; if the traction load active power prediction value is greater than or equal to 0, and less than or equal to the new energy output prediction value, or the traction load active power prediction value is greater than the preset charging threshold, and less than 0, the determination result is the charging state in the new energy electric energy recovery mode; if the traction load active power prediction value is less than or equal to the preset charging threshold, the determination result is the charging state in the valley filling working mode.

[0010] Preferably, the power of the energy storage system under different working states is calculated using the following expressions:

[0011] P 1 (t) = P(t) - P dis -P R (t)

[0012] P 2(t) = 0

[0013] P 3 (t) = P(t) - P R (t)

[0014] P 4 (t)=-P R (t)

[0015] P 5 (t) = P(t) - P ch -P R (t)

[0016] Among them, P 1 Indicates the energy storage system power in the discharge state under the peak shaving working mode, P 2 Indicates the energy storage system power in standby mode, P 3 and P 4 They represent the energy storage system power in different charging states under different modes of recycling new energy electricity, P 5 represents the energy storage system power in the charging state under the valley filling working mode, P represents the active power of the traction load, P dis Indicates the preset discharge threshold, P R Represents the predicted value of new energy output, P ch represents the preset charging threshold, and t represents the time.

[0017] Preferably, in the step of obtaining reactive power for improving the power factor of the substation and active power for reducing the negative sequence current of the substation, it includes: using the predicted value of the new energy output and the calculated power to calculate the reactive power, and further using the predicted value of the new energy output, the calculated power, and the calculated reactive power to calculate the active power.

[0018] Preferably, the reactive power is calculated using the following expression:

[0019]

[0020] Among them, Q r Indicates the reactive power transferred by the interface, E indicates the interface capacity, and P R Represents the predicted value of new energy output, P ES represents the calculated power, Q represents the predicted reactive power of the traction load, and t represents time.

[0021] Preferably, the active power is calculated using the following expression:

[0022]

[0023] Among them, Pr Indicates the active power transferred by the interface, P α It represents the predicted value of active power of traction load in phase α, P β It represents the predicted value of active power of β-phase traction load.

[0024] Preferably, the type of renewable energy power generation connected to the target substation is photovoltaic, wherein the step of obtaining the predicted value of renewable energy output for a specified time period includes: using the collected historical photovoltaic output and historical light data to determine the correlation between photovoltaic output and light data; using the collected historical light data to determine the change characteristics of the light data to obtain the predicted value of light intensity for the specified time period; substituting the predicted value of light intensity for the specified time period into the correlation to obtain the corresponding predicted value of photovoltaic output.

[0025] On the other hand, the present invention also provides an energy management system for accessing new energy to an active traction substation, the energy management system comprising the following modules: a data processing module, which is used to collect historical new energy output and historical meteorological data, historical traction load data and driving operation diagrams of the target substation to obtain new energy output forecast values ​​and traction load power forecast values ​​for a specified time period; a working state determination module, which is used to configure preset charging and discharging thresholds for the target substation that match different degrees of traction load demand, so as to determine the working state of the energy storage system in the specified time period in combination with each predicted value, and calculate the power of the energy storage system in the current working state; an interface capacity configuration module, which is used to obtain the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation according to the predicted values ​​and the calculated power, and based on this, determine the interface capacity, wherein the interface is the energy transmission channel from the energy storage system to the target substation.

[0026] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0027] The present invention provides an energy management strategy for accessing new energy to an active traction substation. The energy management strategy first predicts the output of new energy and the traction load power by collecting historical working data of the target substation; then, according to each predicted value, the working state of the energy storage system is predicted, and the power of the energy storage system under the predicted working state is calculated; finally, according to each predicted value and the calculated power, the reactive power for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation transferred by the energy transmission channel (interface) from the energy storage system to the target substation are obtained, and the interface capacity is further determined. The present invention effectively realizes the energy management and capacity configuration of the access of new energy to the energy storage system, improves the utilization rate of train regenerative braking energy, effectively reduces the maximum load demand of the traction substation, and reduces the comprehensive cost of electrified railways, which can better meet the actual engineering needs.

[0028] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0030] Figure 1 It is a step diagram of the energy management strategy for connecting new energy to an active traction substation according to an embodiment of the present application.

[0031] Figure 2 It is a topological structure diagram of an electrified railway energy storage system according to an energy management strategy for accessing new energy to an active traction substation in an embodiment of the present application.

[0032] Figure 3 It is a flow chart for solving the objective function of the energy management strategy for connecting new energy to an active traction substation according to an embodiment of the present application.

[0033] Figure 4 It is a module block diagram of the energy management system for accessing new energy to an active traction substation according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0035] In addition, the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be performed in an order different from that shown here.

[0036] At present, the interface capacity configuration strategy and management of electrified railway energy storage mainly include: (1) Single energy storage uses a single fixed threshold peak-shaving and valley-filling interface capacity configuration strategy for capacity optimization, which cannot take into account the basic electricity fee and electricity fee benefits (the discharge threshold is too low, which cannot effectively reduce the maximum demand and cannot guarantee the basic electricity fee benefits; the discharge threshold is too high, the utilization rate of regenerative braking energy is low, and the electricity fee benefits cannot be guaranteed); (2) The energy storage medium mainly adopts a multi-threshold and allocation ratio interface capacity configuration strategy, which can take into account the requirements of railway load energy density and power density and obtain better economic benefits, but in actual applications, there are problems such as high initial investment cost, long payback period, and relatively complex control. In addition, the management of electrified railway new energy systems is mainly solved with the goal of maximizing net benefits. In actual engineering applications, there are also problems such as high initial investment cost and long investment payback period.

[0037] Therefore, in order to solve the above problems, the present invention proposes an energy management strategy for accessing new energy to an active traction substation. The energy management strategy first predicts the output of new energy and the traction load power by collecting the historical working data of the target substation; then, according to each predicted value, the working state of the energy storage system is predicted, and the power of the energy storage system under the predicted working state is calculated; finally, according to each predicted value and the calculated power, the reactive power transferred from the energy storage system to the target substation for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation are obtained, and the interface capacity is further determined. The present invention effectively realizes the energy management and capacity configuration of the access of new energy to the energy storage system, improves the utilization rate of train regenerative braking energy, effectively reduces the maximum load demand of the traction substation, reduces the comprehensive cost of electrified railways, and can better meet actual engineering needs.

[0038] Embodiment 1

[0039] Figure 1This is a step diagram of the energy management strategy for connecting new energy to an active traction substation in an embodiment of the present application. Figure 1 To illustrate the various steps of this method.

[0040] like Figure 1 As shown, in step S110, the historical renewable energy output and historical meteorological data, historical traction load data and train operation diagram of the target substation are collected to obtain the predicted value of renewable energy output and traction load power in the specified period. In order to achieve energy conservation and emission reduction, cost saving and consumption reduction in railways, renewable energy power generation and energy storage systems are usually arranged as follows: Figure 2 The method shown is connected to the traction power supply system together ( Figure 2 It is a topological structure diagram of the electrified railway energy storage system of the energy management strategy of the new energy access active traction substation of the embodiment of the present application). Specifically, this embodiment collects the historical new energy output of the target substation (for example: the historical output power of renewable energy) and the historical meteorological data of the area where the target substation is located, predicts the output of renewable energy, and obtains the new energy output prediction value for the specified time period. At the same time, the historical traction load data and the driving operation diagram of the target substation are collected to form the curve of the change of the active power of the traction load of the target substation with the driving state and the curve of the change of the reactive power with the driving state, so as to predict the active power and reactive power of the traction load according to the formed curves, respectively, and obtain the traction load power prediction value for the specified time period (in the same time period as the aforementioned new energy output prediction value).

[0041] In a specific embodiment of the present application, the target substation is an active traction substation.

[0042] Further, in step S120, preset charge and discharge thresholds matching the demand of traction loads at different levels are configured for the target substation, so as to combine each predicted value to determine the working state of the energy storage system during a specified period and calculate the power of the energy storage system in the current working state. Specifically, in this embodiment, the daily traction load is divided into a high-demand period and a low-demand period based on the historical train operation diagram of the target substation. Thus, by configuring preset charge and discharge thresholds matching the demand of traction loads at different levels for the target substation, the energy storage system can maintain a high discharge threshold and a matching charge threshold during the high-demand period to effectively reduce the maximum demand, and maintain a low discharge threshold and a matching charge threshold during the low-demand period to improve the utilization rate of regenerative braking energy. Then, using the predicted value of new energy output and the predicted value of traction load power during the specified period obtained in step S110, and the corresponding preset charge and discharge thresholds, the working state of the energy storage system during the specified period is determined, so as to control the energy storage system to operate according to the determined working state. After obtaining the determination result, this embodiment also calculates the power of the energy storage system in the current working state to configure the capacity of the power supply system where the energy storage system is located, thereby realizing energy management and capacity configuration and effectively ensuring economic benefits.

[0043] The working state of the energy storage system is determined in sequence according to the discharge state in the peak shaving working mode, the standby state in the standby working mode, the charging state in the new energy power recovery mode, and the charging state in the valley filling working mode. Among them, in the step of determining the working state of the energy storage system during a specified period, if the difference between the predicted value of the traction load active power and the preset discharge threshold is greater than or equal to the predicted value of the new energy output, that is: P(t) - P dis ≥P R (t), the determination result is the discharge state in the peak shaving working mode; if the predicted value of the new energy output is greater than the difference between the predicted value of the traction load active power and the preset discharge threshold and less than the predicted value of the traction load active power, that is: P(t) - P dis <P R (t) < P(t), the determination result is the standby state in the standby working mode; if the predicted value of the traction load active power is greater than or equal to 0 and less than or equal to the predicted value of the new energy output, that is: 0 ≤ P(t) ≤ P R (t), at this time, the new energy power is preferentially supplied to the train traction, and the energy storage system absorbs the remaining new energy power under the constraint conditions of power and capacity, or the predicted value of the traction load active power is greater than the preset charge threshold and less than 0, that is: P ch<P(t)<0, at this time, new - energy electric energy is not preferentially supplied to train traction. The energy - storage system directly absorbs new - energy electric energy under the constraint conditions of power and capacity, and the determination result is the charging state in the new - energy - electric - energy recovery mode; if the predicted value of the active power of the traction load is less than or equal to the preset charging threshold, that is: P(t)≤P ch , at this time, the energy - storage system preferentially absorbs the regenerative braking energy P(t)-P ch , and then absorbs the new - energy electric energy -P R (t), then the determination result is the charging state in the valley - filling operation mode.

[0044] In the embodiments of the present application, the power of the energy - storage system in different working states is calculated by using the following expressions respectively:

[0045] P 1 (t)=P(t)-P dis -P R (t) (1)

[0046] P 2 (t)=0 (2)

[0047] P 3 (t)=P(t)-P R (t) (3)

[0048] P 4 (t)=-P R (t) (4)

[0049] P 5 (t)=P(t)-P ch -P R (t) (5)

[0050] Among them, P 1 represents the power of the energy - storage system in the discharge state in the peak - shaving operation mode, P 2 represents the power of the energy - storage system in the standby state in the standby operation mode, P 3 and P 4 respectively represent the power of the energy - storage system in the charging state in different new - energy - electric - energy recovery modes, P 5 represents the power of the energy - storage system in the charging state in the valley - filling operation mode, P represents the active power of the traction load, P dis represents the preset discharge threshold, P R represents the predicted value of new - energy output, P ch represents the preset charging threshold, and t represents time.

[0051] Further, in step S130, the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation are obtained according to the predicted values ​​and the calculated power, and based on this, the interface capacity is determined, wherein the interface is the energy transmission channel from the energy storage system to the target substation. Figure 2 In the embodiment of the present application, based on the basic operating parameters of the energy storage system (e.g., maximum discharge power, maximum charging power, energy storage state of charge SOC variation range, etc.), the new energy output prediction value and traction load power prediction value of the specified time period obtained in step S110, as well as the power of the energy storage system obtained in step S120, are used to obtain the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation, that is, the power prediction value corresponding to the specified time period. Finally, the interface capacity of the energy storage system actually connected to the target substation in the specified time period is determined according to the new energy output prediction value and the aforementioned power prediction value.

[0052] In a specific embodiment of the present application, the priority of interface capacity energy transfer is from high to low: new energy output (used to save the target substation electricity fee), reactive power used to improve the substation power factor, and active power used to reduce the negative sequence current of the substation. It can be seen that the present invention first ensures that the interface capacity is used to reduce the target substation energy consumption, and secondly ensures that the remaining interface capacity is used to improve the power quality of the power supply, which brings additional economic benefits without reducing the power quality, and has stronger economy and practicality.

[0053] Next, in the step of obtaining reactive power for improving the power factor of the substation and active power for reducing the negative sequence current of the substation, the reactive power is calculated using the predicted value of the output of new energy and the calculated power, and the active power is further calculated using the predicted value of the output of new energy, the calculated power, and the calculated reactive power. Specifically, this embodiment uses the calculated power as the expected power of the energy storage system in the specified time period, so as to perform a first calculation of the remaining interface capacity according to the predicted value of the output of renewable energy and the expected power of the energy storage system in the specified time period. At this time, the remaining interface capacity that needs to be calculated is transferred to the reactive power used to improve the power factor of the substation. After the reactive power calculation is completed, this embodiment again uses the predicted value of the output of new energy and the expected power of the energy storage system in the specified time period, and combines the calculated reactive power to perform a second calculation of the remaining interface capacity. At this time, the remaining interface capacity that needs to be calculated is transferred to reduce the active power of the negative sequence current of the substation by balancing the two-phase power. Based on this, this embodiment uses the interface capacity corresponding to the new energy output prediction value and the sum of the remaining interface capacity obtained through two calculations to achieve the purpose of determining the interface capacity in the specified period.

[0054] In the embodiment of the present application, the reactive power is calculated using the following expression:

[0055]

[0056] Among them, Q r Indicates the reactive power transferred by the interface, E indicates the interface capacity, and P ES represents the calculated power, and Q represents the predicted reactive power of the traction load.

[0057] In the embodiment of the present application, the active power is calculated using the following expression:

[0058]

[0059] Among them, P r Indicates the active power transferred by the interface, P α It represents the predicted value of active power of traction load in phase α, P β It represents the predicted value of active power of β-phase traction load.

[0060] After determining the capacity of the interface, the present invention also takes the net income, investment recovery period and rate of return as the objective function, and establishes the full life cycle economic model of the power supply system where the energy storage system is located, so as to optimize the current interface capacity by solving the objective function, and obtain the corresponding optimal new energy installed capacity and optimal energy storage access capacity. Specifically, this embodiment takes into account the basic electricity fee and electricity fee income, determines the objective function with net income, investment recovery period and rate of return as the optimization target, and establishes the full life cycle economic model of the power supply system where the energy storage system is located based on the aforementioned energy management strategy. Afterwards, using the preset new energy installed capacity, the preset energy storage access capacity (the electric energy that can be released by the energy storage unit), the preset charge and discharge threshold and the current interface capacity, combined with the capacity configuration parameters and energy management parameters of the power supply system where the energy storage system is located with the aforementioned interface capacity as a variable, the objective function is solved, and the optimization of the current interface capacity is completed accordingly, and the corresponding optimal new energy installed capacity and optimal energy storage access capacity are obtained.

[0061] In the embodiment of the present application, the full life cycle economic model is expressed by the following expression:

[0062]

[0063] Among them, F 1 represents net income, N represents the project period, T represents the year, and R T Indicates annual electricity savings, C om.T represents the annual operating cost, C con represents the initial investment cost, F 2 represents the payback period, T PP represents the payback period, F3 Indicates the rate of return.

[0064] This embodiment uses the preset new energy installed capacity, the preset energy storage access capacity, the preset charge and discharge threshold and the current interface capacity as variables, and uses an optimization algorithm to solve the objective function to obtain a Pareto solution set. Then, the optimal solution is selected from the current Pareto solution set. Figure 3 , which is a flow chart for solving the objective function of the energy management strategy for connecting new energy to an active traction substation in an embodiment of the present application. Figure 3 , the process of solving the objective function is described in detail. In the embodiment of the present application, the process of solving the objective function includes the following steps: S1, initialization parameters, including the population number N p , the maximum number of iterations G n , Factor C r , calculate the value of each objective function; S2, select N from the current population through the binary tournament p / 2 dominant individuals are used as the parent population for genetic and mutation operations, producing N p / 2 offspring populations;

[0065] S3, calculate the objective function value of each offspring population; S4, N p / 2 offspring populations are merged with the current population, non-dominated sorting is performed and the crowding distance is calculated; S5, N p / 2 dominant individuals as the next generation population; S6, determine the termination condition: if the number of iterations reaches the maximum evolutionary generation, terminate the loop, otherwise enter S2.

[0066] Next, the fuzzy set of the Pareto solution set is calculated by the membership function using the following expression:

[0067]

[0068] Among them, δ i represents the fuzzy set of Pareto solution set, h i , max represents the maximum value of the i-th objective function of the Pareto solution set, h i，min represents the minimum value of the i-th objective function of the Pareto solution set, h i represents the objective function value of the i-th non-dominated solution.

[0069] Finally, the fuzzy membership of the jth non-dominated solution in the Pareto solution set is calculated using the following expression, and the solution with the largest fuzzy membership is taken as the corresponding capacity allocation plan:

[0070]

[0071] Among them, Ng represents the number of optimization targets, δ i，j represents the fuzzy membership of the jth objective value of the ith non-dominated solution, and J represents the total number of non-dominated solutions.

[0072] In a specific embodiment of the present application, the solution to the objective function must at least meet the following preset constraints: interface capacity constraint, energy storage maximum charging and discharging power constraint, energy storage real-time power constraint, power balance constraint, and installed capacity constraint.

[0073] In a specific embodiment of the present application, the type of renewable energy power generation connected to the target substation includes one or more of photovoltaic, wind power and hydrogen energy. The type of energy storage system includes one or more of lithium battery, super capacitor and flywheel.

[0074] In summary, the present invention can effectively reduce the electricity cost expenditure of the traction substation, and configure the capacity based on the net income, investment payback period and rate of return of the power supply system in which the energy storage system is located as the optimization target, thereby avoiding the problems of large initial investment cost and long investment payback period in actual engineering applications, and obtaining a larger basic electricity cost income and electricity cost income.

[0075] In a specific embodiment of the present application, the type of new energy power generation connected to the target substation is photovoltaic, and the type of energy storage system is lithium titanate battery. The above photovoltaic and lithium titanate batteries are connected to the current target substation based on the railway power conditioner. At this time, in the step of obtaining the predicted value of the new energy output for a specified period of time, first, the collected historical photovoltaic output and historical light data are used to determine the correlation between the photovoltaic output and the light data; then, the collected historical light data is used to determine the change characteristics of the light data, and the light intensity prediction value for the specified period of time is obtained; finally, the light intensity prediction value for the specified period of time is substituted into the correlation to obtain the corresponding photovoltaic output prediction value.

[0076] Specifically, this embodiment first uses the collected historical photovoltaic output and historical light data to form a curve of photovoltaic output changing with light data, thereby determining the correlation between photovoltaic output and light data. Afterwards, the collected historical light data is used to form a curve of light data changing with time, thereby determining the change characteristics of the light data, that is, the correlation between light data and time, and then substituting the specified time period into the correlation between light data and time, the light intensity prediction value of the specified time period can be obtained. Finally, the light intensity prediction value of the specified time period is substituted into the correlation between photovoltaic output and light data, and the corresponding photovoltaic output prediction value can be obtained.

[0077] In the embodiment of the present application, the correlation between photovoltaic output and light data is expressed by the following expression:

[0078]

[0079] Among them, P pv Represents the predicted value of photovoltaic output, It represents the rated power of photovoltaic, I represents the light intensity, I max Indicates the maximum light intensity.

[0080] Embodiment 2

[0081] Based on the energy management strategy for connecting new energy to active traction substations described in the first embodiment above, an embodiment of the present invention further provides an energy management system for connecting new energy to active traction substations (hereinafter referred to as “energy management system”). Figure 4 It is a module block diagram of the energy management system for accessing new energy to an active traction substation according to an embodiment of the present application.

[0082] like Figure 4 As shown, the energy management system in the embodiment of the present invention includes: a data processing module 41, a working state determination module 42 and an interface capacity configuration module 43. The data processing module 41 is implemented according to the method described in step S110 above, and is configured to collect the historical new energy output and historical meteorological data, historical traction load data and driving diagram of the target substation to obtain the new energy output prediction value and traction load power prediction value of the specified period; the working state determination module 42 is implemented according to the method described in step S120 above, and is configured to configure the target substation with preset charge and discharge thresholds that match the traction load demand of different degrees, so as to determine the working state of the energy storage system in the specified period in combination with each prediction value, and calculate the power of the energy storage system in the current working state; the interface capacity configuration module 43 is implemented according to the method described in step S130 above, and is configured to obtain the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation according to each prediction value and the calculated power, and based on this, determine the interface capacity, wherein the interface is the energy transmission channel from the energy storage system to the target substation.

[0083] The present invention discloses an energy management strategy for accessing new energy to an active traction substation. The energy management strategy first predicts the output of new energy and the traction load power by collecting the historical working data of the target substation; then, according to each predicted value, the working state of the energy storage system is predicted, and the power of the energy storage system under the predicted working state is calculated; finally, according to each predicted value and the calculated power, the reactive power transferred by the energy transmission channel (interface) from the energy storage system to the target substation for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation are obtained, and the interface capacity is further determined. The present invention effectively realizes the energy management and capacity configuration of the access of new energy to the energy storage system, improves the utilization rate of train regenerative braking energy, effectively reduces the maximum load demand of the traction substation, and reduces the comprehensive cost of electrified railways, and can better meet the actual engineering needs.

[0084] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any person familiar with the technology within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0085] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims of the present invention.

[0086] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0087] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. An energy management strategy for connecting new energy to an active traction substation, characterized in that: include: Collect historical renewable energy output and historical meteorological data, historical traction load data and vehicle operation diagrams of the target substation to obtain the predicted renewable energy output and traction load power for a specified period of time; Configure preset charge and discharge thresholds for the target substation that match different levels of traction load demand, so as to determine the working state of the energy storage system in the specified time period in combination with the predicted values, and calculate the power of the energy storage system in the current working state; According to the predicted values ​​and the calculated power, the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation are obtained, and based on this, the interface capacity is determined, wherein the interface is the energy transmission channel from the energy storage system to the target substation.

2. The energy management strategy according to claim 1, characterized in that: After determining the capacity of the interface, the energy management strategy further includes: Taking net income, investment payback period and rate of return as objective functions, a full life cycle economic model of the power supply system in which the energy storage system is located is established, so that by solving the objective function, the current interface capacity is optimized and the corresponding optimal new energy installed capacity and optimal energy storage access capacity are obtained.

3. The energy management strategy according to claim 2, characterized in that: The life cycle economic model is expressed using the following expression: Among them, F1 represents net income, N represents project period, T represents year, R represents T Indicates annual electricity savings, C om.T represents the annual operating cost, C con represents the initial investment cost, F2 represents the investment payback period, T PP represents the payback period, and F3 represents the rate of return.

4. The energy management strategy according to any one of claims 1 to 3, characterized in that: The working state is determined in the order of the discharge state in the peak shaving working mode, the standby state in the standby working mode, the charging state in the new energy power recovery mode, and the charging state in the valley filling working mode. The step of determining the working state of the energy storage system in the specified time period includes: If the difference between the predicted value of the active power of the traction load and the preset discharge threshold is greater than or equal to the predicted value of the new energy output, the determination result is the discharge state under the peak shaving working mode; If the new energy output prediction value is greater than the difference between the traction load active power prediction value and the preset discharge threshold, and is less than the traction load active power prediction value, the determination result is the standby state under the standby working mode; If the predicted value of the active power of the traction load is greater than or equal to 0 and less than or equal to the predicted value of the output of the new energy source, or the predicted value of the active power of the traction load is greater than the preset charging threshold and less than 0, the determination result is the charging state in the mode of recovering new energy electric energy; If the predicted value of the active power of the traction load is less than or equal to the preset charging threshold, the determination result is the charging state in the valley filling working mode.

5. The energy management strategy according to claim 4, characterized in that: The power of the energy storage system under different working conditions is calculated using the following expressions: P1(t)=P(t)-P dis -P R (t) P2(t)=0 P3(t)=P(t)-P R (t) P4(t)=-P R (t) P5(t)=P(t)-P ch -P R (t) Among them, P1 represents the energy storage system power in the discharge state under the peak shaving working mode, P2 represents the energy storage system power in the standby state under the backup working mode, P3 and P4 represent the energy storage system power in the charging state under different new energy recovery modes, P5 represents the energy storage system power in the charging state under the valley filling working mode, P represents the active power of the traction load, P dis Indicates the preset discharge threshold, P R Represents the predicted value of new energy output, P ch represents the preset charging threshold, and t represents the time.

6. The energy management strategy according to any one of claims 1 to 5, characterized in that: The step of obtaining reactive power for improving the power factor of the substation and active power for reducing the negative sequence current of the substation includes: The reactive power is calculated using the predicted output value of the new energy and the calculated power, and the active power is further calculated using the predicted output value of the new energy, the calculated power, and the calculated reactive power.

7. The energy management strategy according to claim 6, characterized in that: The reactive power is calculated using the following expression: Among them, Q r Indicates the reactive power transferred by the interface, E indicates the interface capacity, and P R Represents the predicted value of new energy output, P ES represents the calculated power, Q represents the predicted reactive power of the traction load, and t represents time.

8. The energy management strategy according to claim 7, characterized in that: The active power is calculated using the following expression: Among them, P r Indicates the active power transferred by the interface, P α It represents the predicted value of active power of traction load in phase α, P β It represents the predicted value of active power of β-phase traction load.

9. The energy management strategy according to any one of claims 1 to 8, characterized in that: The type of renewable energy power generation connected to the target substation is photovoltaic, wherein the step of obtaining the predicted value of renewable energy output in a specified period includes: Using the collected historical photovoltaic output and historical sunlight data, determine the correlation between photovoltaic output and sunlight data; Using the collected historical illumination data, determining the change characteristics of the illumination data, and obtaining the illumination intensity prediction value for the specified time period; The light intensity prediction value of the specified time period is substituted into the correlation relationship to obtain the corresponding photovoltaic output prediction value.

10. An energy management system for connecting new energy to an active traction substation, characterized in that: The energy management system includes the following modules: A data processing module is used to collect historical renewable energy output and historical meteorological data, historical traction load data and vehicle operation diagrams of the target substation to obtain a predicted renewable energy output value and a predicted traction load power value for a specified period of time; A working state determination module, which is used to configure preset charge and discharge thresholds matching different degrees of traction load demand for the target substation, thereby combining various predicted values ​​to determine the working state of the energy storage system in the specified time period, and calculate the power of the energy storage system in the current working state; An interface capacity configuration module is used to obtain the reactive power transferred by the interface for improving the power factor of the substation and the active power for reducing the negative sequence current of the substation according to the predicted values ​​and the calculated power, and based on this, determine the interface capacity, wherein the interface is the energy transmission channel from the energy storage system to the target substation.

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