CN116565908A - Flexible traction substation energy management method for photovoltaic and energy storage system access - Google Patents
Flexible traction substation energy management method for photovoltaic and energy storage system access Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
- H02J2300/26—The renewable source being solar energy of photovoltaic origin involving maximum power point tracking control for photovoltaic sources
Abstract
The invention discloses a flexible traction substation energy management method for photovoltaic and energy storage system access, which comprises the following steps: dividing the energy management scheme into three time scales of day front, day inner and real time; in a day-ahead optimal scheduling stage, based on train traction load and photovoltaic output short-term prediction data, taking the lowest comprehensive operation cost of a traction substation as an objective function, constructing constraint conditions for ensuring normal operation of the traction substation, and establishing a mixed integer linear programming model of day-ahead power flow optimal scheduling; in the daily rolling optimization stage, rolling correction of an energy storage system work plan is completed by taking the minimum power supply plan deviation of a traction substation as an objective function and controlling normal operation of the substation in a time domain to construct constraint conditions based on a model prediction control method; in a real-time optimizing operation stage, a photovoltaic flexible output scheme is considered, a nonlinear optimizing model with the lowest negative sequence current of the primary side of the traction substation is established, and a real-time power compensation instruction of the back-to-back converter is solved.
Description
Technical Field
The invention belongs to the technical field of traction power supply system energy management, and particularly relates to a flexible traction substation energy management method for photovoltaic and energy storage system access.
Background
Along with the development planning of modern urban financial circles, the transportation travel demands of passengers are also rapidly increased. Therefore, the construction scale of electrified railways in China is continuously increased, and the scale of a planned long-term railway network reaches 20 kilometers, wherein the high-speed railway is 7 kilometers. However, while electrified railways are rapidly evolving, their power consumption needs are also increasing.
Under the background, by connecting the photovoltaic power generation system and the energy storage system in the traction substation, the new energy power generation resource along the railway and the train regenerated braking energy are effectively utilized, the comprehensive operation cost of the traction substation is reduced, and the negative sequence current compensation is realized, so that the method has become one of research hotspots in the railway industry. However, train traction load fluctuates drastically (up to 10MW in seconds) and photovoltaic output also has uncertainty, which presents a greater challenge for the energy management scheme of the system. Therefore, for the traction substation with the optical storage access, the energy management scheme which can overcome the randomness of traction load and photovoltaic output, realize the economic and optimal operation of the traction substation, has the capability of compensating negative sequence current in real time and realizes friendly interaction with a three-phase power grid is needed to be solved.
Disclosure of Invention
The invention aims to solve the technical problems in the background technology, and aims to provide an energy management method of a flexible traction substation, which is accessed by a photovoltaic and energy storage system, can overcome adverse effects caused by traction load and photovoltaic output prediction errors, improve the economic and optimal operation capacity of the traction substation, effectively realize real-time compensation of primary negative sequence current of the substation, and is beneficial to friendly interaction with a three-phase power grid.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a method of flexible traction substation energy management for photovoltaic and energy storage system access, the system energy management strategy being divided into three time scales, the method comprising:
s1: in a day-ahead optimal scheduling stage, based on train traction load and photovoltaic output short-term prediction data, taking the lowest comprehensive operation cost of a traction substation as an objective function, constructing constraint conditions for ensuring normal operation of the traction substation, and establishing a mixed integer linear programming model of day-ahead power flow optimal scheduling;
s2: in the daily rolling optimization stage, taking the minimum power supply plan deviation of the traction substation as an objective function, and constructing constraint conditions for controlling the normal operation of the substation in a time domain to construct a model predictive control scheme of the flexible traction substation;
S3: in a real-time optimizing operation stage, a photovoltaic flexible output scheme is considered, a nonlinear optimizing model with the lowest negative sequence current of the primary side of the traction substation is established, a real-time power compensation instruction of the back-to-back converter is solved, and a real-time optimizing operation method of the flexible traction substation is established.
Further, before the step S1, the method further includes: the energy management method is divided into three time scales of day before, day in and real time.
Further, a traction load and photovoltaic prediction method is adopted to obtain short-term prediction data of the train load and the photovoltaic output of the power supply arms at the left side and the right side of the traction substation in the dispatching day;
the objective function of the mixed integer linear programming model for establishing the daily trend optimization scheduling is as follows:
wherein: c (C) DA To adjust the total running cost of the day; c G,b 、c G,s Respectively, are tractionThe electricity purchasing price of the substation and the electricity fee price of the return three-phase power grid are guided; c D The price of the electricity charge is the required quantity; c Ess 、c PV The operation and maintenance costs of the energy storage and photovoltaic system are respectively;the power purchasing power and the returning power of the traction substation from the three-phase power grid at the moment t are respectively; p (P) Dem Is the maximum required power; />Respectively charging and discharging power of the energy storage system at the moment t; />The power output value of the photovoltaic power generation system at the moment t is; t is the dispatching time period number of the day-ahead tide optimization dispatching stage; Δt is the time scale of the day-ahead optimal scheduling phase.
Further, according to the flexible traction substation model and based on the train load and the photovoltaic output short-term prediction data, a constraint condition of a day-ahead tide optimization scheduling stage is established, and the method comprises the following steps: the power balance constraint of the substation, the power constraint of a primary side common connection point, namely a PCC point, the capacity constraint of the back-to-back converter, the charge and discharge power constraint of the energy storage system, the state of charge constraint of the energy storage medium and the maximum demand power constraint.
Further, after a mixed integer linear programming model of a day-ahead power flow optimizing and scheduling stage is established, solving the model to obtain a power substation PCC point power plan, an energy storage system charge-discharge power plan and an energy storage medium charge state plan, namely, completing day-ahead power flow optimizing and scheduling of the flexible traction substation accessed by the photovoltaic and energy storage system, and issuing the scheduling plan to a day-ahead rolling optimizing and operating stage in advance.
Further, the model predictive control method for establishing the k moment of the flexible traction substation in the daily rolling optimization operation stage specifically comprises the following steps:
selecting a vector formed by PCC point power at k moment of flexible traction substation, charging and discharging power of energy storage system and state of chargeIs a state vector; selecting increment of energy storage system output at k moment of flexible traction substation relative to planned value before day >Is a control vector; selecting increment constitution vector of ultra-short-term predicted power curve of total load and photovoltaic output of left and right power supply arm trains at k moment of flexible traction substation relative to day-ahead predicted curveIs a disturbance vector; selecting a vector formed by PCC point power at k moment of a flexible traction substation and state of charge of an energy storage system>For outputting vectors, establishing a prediction model of a flexible traction substation model prediction control method at the moment k:
wherein: η (eta) Ess The charge and discharge efficiency of the energy storage system is improved; Δk is the time scale of the intra-day scroll optimization phase.
Further, ultra-short-term prediction data of traction load and photovoltaic output in a prediction time domain are obtained from k+1 time to k+P time, and the ultra-short-term prediction time domain is gradually iterated by the middle prediction model to construct an output vector matrix in the prediction time domain as follows:
Y k ＝[y k+1 ,y k+2 ,…,y k+P ] T
wherein: y is k+p (p=1, P) is an output vector formed by the power of the PCC point of the substation and the state of charge of the energy storage system at the moment k+p, which is predicted by the prediction model at the moment k;
based on the obtained traction load and photovoltaic output ultra-short-term prediction data, selecting k+1 time to k+M time of the flexible traction substation as a control time domain, wherein the control time domain is required to be smaller than or equal to a prediction time domain, namely M is less than or equal to P, and establishing an optimization target of a k time model prediction control method as follows:
Wherein:for the tracking plan target matrix of k moment control time domain output vector, by every moment in time domain corresponding to power value ++f of PCC point in day-ahead plan>Energy storage state of charge-> Constructing; deltaU k For the control matrix in k time control time domain, the increment of energy storage power relative to day-ahead plan at each time in the time domainConstructing; w, Q is a matrix of weight coefficients.
Further, according to the flexible traction substation model and based on the ultra-short-term prediction data of the load and the photovoltaic output obtained in the above, the constraint condition under the normal operation condition of the control time domain of the flexible traction substation is established, which comprises the following steps: power balance constraint of the substation, primary side public connection point power constraint, back-to-back converter power constraint, energy storage system charge and discharge power constraint, energy storage system state of charge constraint and maximum demand constraint;
according to the prediction model objective function of the obtained model prediction control method and the normal operation constraint condition of the obtained flexible traction transformer station in the control time domain, a quadratic programming model of an optimization operation stage in a day at the moment k is established, the quadratic programming model is solved, a charge and discharge power correction vector of the energy storage system at the moment k+1, k+2, … and k+M is obtained, and correction in the first time period k+1 to k+2 in the vector is transmitted to the energy storage system real-time operation control system.
Further, in the real-time optimizing operation stage, a real-time optimizing operation method of the flexible traction substation at the moment k is constructed, and the method specifically comprises the following steps:
the correction quantity of the energy storage system in the k-1 moment is obtained by a model predictive control method of the flexible traction substation at the k-1 moment, and the daily working plan value of the energy storage system in the k-1 moment is overlapped to obtain the final working plan of the energy storage system in the k-1 moment;
collecting the voltages of the power supply arms at the left side and the right side in real time in the time from k to k+1And->Load current of power supply arms at the left side and the right side>And->Photovoltaic array output voltage current value +.>And->Calculating active power of total load of trains with power supply arms on the left side and the right side +.>And->Reactive power and photovoltaic power generation>Judging whether the phenomenon of returning the PCC point power to the three-phase power grid exists at the current moment, and if the phenomenon of returning does not exist, operating the photovoltaic grid-connected converter in a maximum power point tracking mode; conversely, the photovoltaic power generation system adopts a limited power output mode, and the real-time output power of the photovoltaic power is expressed as follows:
wherein:and (5) obtaining the final working planning value of the energy storage system.
Based on the left power supply arm load and the right power supply arm load acquired in real time and the photovoltaic output power acquired after the control of the photovoltaic grid-connected converter, a negative sequence current real-time optimization compensation objective function is established as follows:
Wherein: k (k) T A transformation ratio of the traction transformer;the total active power of the power supply arms at the alpha and beta phases at the n moments is respectively;the total reactive power of the power supply arms at the time of n is alpha and beta;
according to the flexible traction substation model and based on the obtained load real-time data and photovoltaic control output data, establishing constraint conditions under the normal operation condition of the back-to-back converter, wherein the constraint conditions comprise: power balance constraint of power supply arms on the left side and the right side, power balance constraint of a direct current bus and capacity constraint of a back-to-back converter;
according to the obtained negative sequence current real-time compensation objective function and the obtained back-to-back converter normal operation constraint condition, a nonlinear programming model of an n-moment day optimization operation stage is established, and the model is rapidly solved to obtain a real-time active power compensation instruction of the back-to-back converter at the n momentAnd->Real-time reactive power compensation instruction->And (3) withAnd issues the instruction to a real-time operation control system of the back-to-back converter.
Further, the method further comprises:
obtaining ultra-short-term prediction data of traction load and photovoltaic output in the time k+2 to the time k+P+1, establishing a model prediction control scheme of the flexible traction substation at the time k+1, repeatedly establishing a model prediction control method of the flexible traction substation at the time k in a rolling optimization operation stage in the day, establishing a quadratic programming model of the rolling optimization operation stage in the time k+2 to the time k+M+1, solving the model to obtain a charge and discharge power correction vector of the energy storage system in the time k+2, k+3, … and k+M+1, and transmitting correction quantity of the first time period, namely the time k+2 to k+3, in the vector to the real-time operation control system of the energy storage system, so that the energy storage system is continuously optimized in a rolling way;
The correction quantity of the energy storage system in the k+1 to k+2 moment is obtained by a model predictive control scheme of the k moment of the flexible traction substation, and the daily working plan value of the energy storage system in the k+1 to k+2 moment is overlapped to obtain the final working plan of the energy storage system in the k+1 to k+2 moment; repeating the real-time optimizing operation stage to construct a real-time optimizing operation method of the flexible traction substation at the moment k+1, solving a real-time optimizing operation plan in the moment k+1 to the moment k+2, obtaining a photovoltaic real-time output power instruction in the moment k+1 to the moment k+2, a back-to-back converter real-time active power and reactive power compensation instruction, and issuing the photovoltaic real-time output power instruction, the back-to-back converter real-time active power and reactive power compensation instruction to an operation control system of each converter;
the construction is repeated continuously along with the increase of k, and the energy management method of the flexible traction substation for photovoltaic and energy storage system access is completed.
Compared with the prior art, the invention has the advantages that:
1. according to the invention, the energy management method of the flexible traction substation, which is accessed by the photovoltaic and energy storage system, is divided into three time scales of day before, day in and real time, and day before tide optimal scheduling realizes the effective utilization of the traction substation on the photovoltaic power generation resource and train regenerative braking energy, and improves the economic operation capacity of the traction substation under the two-part system charging scheme;
2. The intra-day rolling optimization stage considers the influence of uncertainty of traction load and photovoltaic output on an operation scheme, reduces operation plan deviation caused by prediction data errors, and improves the energy consumption and maximum demand reduction capacity of the flexible traction substation;
3. the real-time optimization operation stage of the invention considers the negative sequence current real-time optimization compensation method under the rapid fluctuation of the traction load, reduces the primary side negative sequence current of the substation, and meets the real-time operation control requirement of the traction substation.
Drawings
FIG. 1 is a block diagram of a photovoltaic and energy storage system-accessed flexible traction substation of the present invention;
FIG. 2 is a multi-time scale energy management scheme basic framework in the present invention;
FIG. 3 is a flow chart of the photovoltaic flexible output scheme in the real-time optimized operation phase in the invention;
FIG. 4 is a graph of the power of PCC points versus their reference plan power for a power flow optimized scheduling method only before day in an embodiment;
fig. 5 is a graph of PCC power versus its reference plan power for an embodiment of the method of the present invention.
Detailed Description
The following describes specific embodiments of the present invention with reference to examples:
it should be noted that the structures, proportions, sizes and the like illustrated in the present specification are used for being understood and read by those skilled in the art in combination with the disclosure of the present invention, and are not intended to limit the applicable limitations of the present invention, and any structural modifications, proportional changes or size adjustments should still fall within the scope of the disclosure of the present invention without affecting the efficacy and achievement of the present invention.
Also, the terms such as "upper," "lower," "left," "right," "middle," and "a" and the like recited in the present specification are merely for descriptive purposes and are not intended to limit the scope of the invention, but are intended to provide relative positional changes or modifications without materially altering the technical context in which the invention may be practiced.
Example 1:
the structure of the flexible traction substation to which the invention is directed is shown in fig. 1, and the basic framework of the energy management scheme of the flexible traction substation to which the photovoltaic and energy storage system is connected is shown in fig. 2.
The method specifically comprises the following steps:
step 1: in a day-ahead tide optimization scheduling stage, a cyclic neural network prediction model is adopted to obtain prediction data of the active power of the power supply arm train load at the left side and the right side of the traction substation in the scheduling day; acquiring meteorological data and illumination radiation data in a dispatching day from a local meteorological department, and obtaining photovoltaic output prediction data by adopting a direct prediction model;
step 2: considering the charge modes of two electricity rates of the electrified railway, the traction substation electric quantity and electric charge parameters comprise electric charge, return electric charge and required electric charge, the operation and maintenance costs of the flexible traction substation accessed by the photovoltaic and energy storage system comprise operation and maintenance electric charge of the energy storage system and operation and maintenance electric charge of the photovoltaic power generation system, and the objective function of the day-ahead power flow optimization scheduling scheme is established according to the charge scheme of the traction substation electric quantity and the operation and maintenance charge as follows:
Wherein: c (C) DA To adjust the total running cost of the day; c G,b 、c G,s The electricity price of the traction substation and the electricity price of the return three-phase power grid are respectively; c D The price of the electricity charge is the required quantity; c Ess 、c PV The operation and maintenance costs of the energy storage and photovoltaic system are respectively;the power purchasing power and the returning power of the traction substation from the three-phase power grid at the moment t are respectively;P Dem is the maximum required power; />Respectively charging and discharging power of the energy storage system at the moment t; />The power output value of the photovoltaic power generation system at the moment t is; t is the dispatching time period number of the day-ahead tide optimization dispatching stage; Δt is the time scale of the day-ahead optimal scheduling phase.
The rapid fluctuation characteristic of the traction load of the train and the scale of the day-ahead tide optimization scheduling problem are comprehensively considered, the time scale of the day-ahead tide optimization scheduling stage is selected to be 1 minute, and the scheduling period T=1440.
Step 3: according to a flexible traction substation model, and based on the train load and photovoltaic output prediction data of the power supply arms on the left side and the right side obtained in the step 1, constraint conditions under normal operation conditions of the flexible traction substation accessed by a photovoltaic system and an energy storage system are established, wherein the constraint conditions comprise primary side active power balance constraint, back-to-back power supply arm active power balance constraint, back-to-back converter middle direct current bus active power balance constraint, active power constraint of primary side public connection points (PCC points) interacting with a three-phase power grid, back-to-back converter active power constraint, energy storage system charge and discharge power constraint, energy storage system charge state constraint and maximum demand constraint of the traction transformer, and specific constraint conditions are as follows:
The traction transformer needs to keep active power balance of the primary side, and the constraint is as follows:
wherein:the total active power of the power supply arms at the alpha phase and the beta phase at the t moment respectively.
The power supply arms on the left side and the right side need to keep active power balance, and the constraint is as follows:
wherein:the active power of the alpha phase-change current transformer and the beta phase-change current transformer in the back-to-back current transformer at the moment t respectively; />And the total active load of the power arm trains at the alpha and beta phases at the t moment respectively.
Active power balance needs to be kept for the middle direct current bus of the back-to-back converter, and the constraint is that:
the primary PCC point interaction power of the traction substation is constrained by the capacity of the traction transformer, and specifically comprises the following steps:
wherein:the power limit value is interacted for the traction substation and the three-phase power grid; />For the time t, representing a binary variable of the interaction power direction of the traction substation and the three-phase power grid, +.>Indicating that the traction substation takes power from the three-phase power grid, < ->Indicating the return of the traction substation to the three-phase power grid.
The back-to-back converter compensates active power to meet the rated capacity constraint of equipment, and specifically comprises the following steps:
wherein:i phase change flow device capacity.
The charging and discharging power of the energy storage system is required to be in the rated charging and discharging power range, and the specific constraint is as follows:
wherein:rated charge and discharge power for the energy storage system; />Binary variable representing charge and discharge states of the energy storage system at time t +. >Indicating that the energy storage system is in a charged state->Indicating that the energy storage system is in a discharged state.
In order to avoid the overcharge and overdischarge of the energy storage medium, the stored energy of the energy storage medium is limited within a certain range; in order to ensure that the day-ahead dispatching stage has periodicity, the consistent start and end states of the energy level of the energy storage system are also required, and the state of charge of the energy storage system is required to meet specific constraints as follows:
wherein:the energy stored by the energy storage system at the moment t; η (eta) Ess,c 、η Ess,d Respectively the charging and discharging efficiency of the energy storage system; />The state of charge of the energy storage system at the moment t; e (E) Ess,r Rated capacity of the energy storage system; />S Ess Respectively the upper limit value and the lower limit value of the charge state of the energy storage system; />The energy levels of the energy storage system at the initial time and the end time of the scheduling day are respectively.
In an electrified railway, the maximum value of the load average value within 15 minutes of a traction substation is taken as the maximum current month demand charge value, and the train operation of the traction substation is assumed to have daily periodicity, so that the maximum demand power on a dispatching day is taken as the current month basic electricity charge value, and the maximum demand needs to meet the constraint condition:
step 4: according to the objective function of the day-ahead power flow optimization scheduling model obtained in the step 2 and the normal operation constraint condition of the flexible traction substation obtained in the step 3, a mixed integer linear programming model of a day-ahead power flow optimization scheduling stage is established, a commercial programming solver, such as an optimization tool CPLEX developed by IBM corporation, is utilized, the solver is called through a Yalmip platform in Matlab environment, the solution of the mixed integer linear programming model is completed, a PCC point active power plan, an energy storage system charge-discharge power plan and an energy storage medium charge state plan under the overall optimal economic operation purpose of the traction substation in a scheduling day are obtained, and the scheduling plan is issued to the day-ahead operation stage in advance, so that day-ahead power flow optimization scheduling of the flexible traction substation accessed by the photovoltaic and energy storage system is completed;
Step 5: in the rolling optimization operation stage in the day, constructing a model predictive control scheme at the k moment of the flexible traction substation:
5.1 selecting a vector formed by PCC point power at k moment of the flexible traction substation (taking electricity from a three-phase power grid by the traction substation to be positive, returning the traction substation to the three-phase power grid to be positive), charging and discharging power of the energy storage system (taking the power in a discharging state to be positive, taking the power in a charging state to be negative) and the state of charge of the energy storage systemIs a state vector; selecting increment of energy storage system output at k moment of flexible traction substation relative to planned value before day>Is a control vector; selecting increment constitution vector of ultra-short-term predicted power curve of total load and photovoltaic output of left and right power supply arm trains at k moment of flexible traction substation relative to day-ahead predicted curve>Is a disturbance vector; selecting a vector formed by PCC point power at k moment of a flexible traction substation and state of charge of an energy storage system>For outputting vectors, a prediction model of the flexible traction substation model prediction control method at the moment k is established as follows:
wherein: η (eta) Ess The charge and discharge efficiency of the energy storage system is improved; Δk is the time scale of the intra-day scroll optimization phase.
5.2 obtaining the ultra-short-term prediction data of the traction load and the photovoltaic output in the prediction time domain from the time point k+1 to the time point k+P, and gradually iterating in the ultra-short-term prediction time domain by the prediction model in 5.1 to construct an output vector matrix in the prediction time domain as follows:
Y k ＝[y k+1 ,y k+2 ,…,y k+P ] T
Wherein: y is k+p (p=1, …, P) is the output vector of the predictive model at time k, which predicts that at time k+p is made up of substation PCC power and energy storage system state of charge.
5.3 selecting k+1 time to k+M time of the flexible traction substation as a control time domain of a model prediction control scheme based on the traction load and photovoltaic output ultra-short-term prediction data obtained in 5.2, and establishing an optimization target of the k time model prediction control method for ensuring effective tracking of the intra-day operation plan of the traction substation on the pre-day scheduling plan, ensuring that the deviation between PCC point power and the pre-day plan is as small as possible, and simultaneously avoiding overlarge power adjustment quantity of an energy storage system, wherein the optimization target is as follows:
wherein:for the tracking plan target matrix of k moment control time domain output vector, by every moment in time domain corresponding to power value ++f of PCC point in day-ahead plan>Energy storage state of charge-> Constructing; deltaU k For the control matrix in k time control time domain, the increment of energy storage power relative to day-ahead plan at each time in the time domainConstructing; w, Q is a matrix of weighting coefficients, wherein to ensure efficient tracking of PCC Point Power over a day-ahead schedule, the weight of PCC Point Power is calculatedThe value needs to be much larger than the weight value of the state of charge of the energy storage system.
In order to reduce the influence degree of traction load and photovoltaic output fluctuation on a PCC point work plan, the economic operation capacity of the flexible traction substation is improved as much as possible, the time scale of the daily rolling optimization stage is selected to be 5 seconds, and the rolling optimization times K=17280; meanwhile, the prediction time domain length in the model prediction control is selected to be 15 minutes, the time period number P=180, the control time domain length is 3 minutes, and the time period number M=36.
5.4, establishing constraint conditions under normal operation conditions of the substation in a control time domain based on the load and photovoltaic output ultra-short-term prediction data obtained in 5.2, wherein the constraint conditions comprise substation power balance constraint, primary side common connection point (PCC point) power constraint, back-to-back converter power constraint, energy storage system charge and discharge power constraint, energy storage system state of charge constraint and maximum demand constraint are as follows:
the traction transformer needs to keep active power balance of the primary side, and the constraint is as follows:
wherein:and the total active power of the power supply arms at the p time alpha and the p time beta are respectively.
The power supply arms on the left side and the right side need to keep active power balance, and the constraint is as follows:
wherein:the active power of the phase-change current transformer at the p moment alpha and the p moment beta respectively; />And the total active load of the power arm trains at the p time alpha and the p phase respectively.
Active power balance needs to be kept for the middle direct current bus of the back-to-back converter, and the constraint is that:
the primary PCC point interaction power of the traction substation is constrained by the capacity of the traction transformer, and specifically comprises the following steps:
wherein:as PCC point interactive power, the traction substation purchases electricity from the three-phase power grid to be positive value, and returns to the three-phase power grid to be negative value; />The power limit value is interacted with the three-phase power grid for the traction substation.
The back-to-back converter compensates active power to meet the rated capacity constraint of equipment, and specifically comprises the following steps:
wherein:i phase change flow device capacity.
The charging and discharging power of the energy storage system is required to be in the rated charging and discharging power range, and the specific constraint is as follows:
wherein:the power of the energy storage system is positive in discharging and negative in charging; />And rated charge and discharge power is provided for the energy storage system.
In order to avoid the occurrence of overcharge and overdischarge of the energy storage medium, the stored energy of the energy storage medium is limited in a certain range, and the specific constraint is as follows:
wherein:the energy stored by the energy storage system at the time p; η (eta) Ess The charge and discharge efficiency of the energy storage system is improved; />The state of charge of the energy storage system at the moment p; e (E) Ess,r Rated capacity of the energy storage system; /> Ess SRespectively the upper limit value and the lower limit value of the charge state of the energy storage system; Δk is the time scale of the intra-day scroll optimization phase.
5.5, establishing a quadratic programming model of an optimization operation stage in a day at k moment according to the model predictive control scheme objective function obtained in 5.3 and the normal operation constraint condition of the flexible traction substation obtained in 5.4, solving the model by using a quadratic programming solver such as a quadratic programming problem solver quadprog function provided by Matlab to obtain a charge and discharge power correction vector of the energy storage system at k+1, k+2, … and k+M moment, and transmitting the correction quantity of the first time period (namely within k+1 to k+2 moment) in the vector to the energy storage system real-time operation control system;
step 6: in the real-time optimizing operation stage, constructing a real-time optimizing operation method of the flexible traction substation at the moment k:
6.1, establishing a model prediction control scheme at the time k-1 of the flexible traction substation in the step 5, solving to obtain a correction quantity of the charging and discharging power of the energy storage system at the time k to the time k+1, and superposing a day-ahead working plan value of the energy storage system at the time k to the time k+1 by the correction quantity to obtain a final working plan of the energy storage system at the time k to the time k+1;
6.2, the voltage of the power supply arms at the left side and the right side is collected in real time in the time from k to k+1 by using a data collection device arranged in the flexible traction substationAnd->Load current of power supply arms at the left side and the right side >And->Photovoltaic array output voltage current value +.>And->Calculating active power of total load of trains with power supply arms on the left side and the right side +.>And->Reactive power and photovoltaic power generation>Because the three-phase power grid adopts a policy of 'returning positive meter' or 'returning non-meter' on the active returning power of the electrified railway traction substation, when the photovoltaic output cannot be absorbed by the train load and the energy storage system, the power grid is directly returned through the back-to-back converter, so that economic benefits are not brought to the operation of the flexible traction substation, the capacity of the back-to-back converter is additionally occupied, and the reduction of the capacity of the back-to-back converter is realizedThe power quality control capability is unfavorable for friendly grid connection of the flexible traction substation. Therefore, in the real-time optimizing operation stage, the actual output value of the photovoltaic power generation system needs to be judged first, the specific method is as shown in fig. 3, whether the phenomenon that the power of the PCC points is returned to the three-phase power grid exists at the current moment is judged according to the real-time information acquisition, if the judgment result shows that the phenomenon that the power of the PCC points is returned to the three-phase power grid does not exist, the photovoltaic grid-connected converter works in a maximum power point tracking mode, and the photovoltaic array is controlled to output the maximum power which can be sent under the current environment condition; conversely, the photovoltaic array adopts a limited power output mode to control the photovoltaic array to send out the required real-time output power, and the real-time output power of the photovoltaic is as follows:
Wherein:the final work plan value of the energy storage system obtained in 6.1.
6.3, based on the left power supply arm load, the right power supply arm load and the photovoltaic output power obtained after the photovoltaic grid-connected converter is controlled, which are acquired and calculated in real time in 6.2, in order to realize friendly interaction between the traction substation and the three-phase power grid, the primary negative sequence current of the substation is reduced, and a negative sequence current real-time optimization compensation objective function is established as follows:
wherein: k (k) T A transformation ratio of the traction transformer;the total active power of the power supply arms at the alpha and beta phases at the n moments is respectively;and the total reactive power of the power supply arms at the alpha phase and the beta phase at the n time respectively.
In order to meet the real-time control requirement, the time scale of the real-time optimization stage is selected to be 1 second, and the number of real-time optimization time periods is n=86400.
6.4, establishing constraint conditions under the normal operation condition of the back-to-back converter according to the flexible traction substation model and based on the load real-time data and the photovoltaic control output data obtained in the step 6.2, wherein the constraint conditions comprise power balance constraint of power supply arms at the left side and the right side, power balance constraint of a direct current bus and capacity constraint of the back-to-back converter, and the constraint conditions are as follows:
the power supply arms on the left side and the right side are required to meet active power balance and reactive power balance, and the constraint is as follows:
Wherein:the total active load and the total reactive load of the power arm train are respectively n moment i phases; />The active compensation power and the reactive compensation power of the i-phase current transformer in the n-moment back-to-back converter are respectively.
Active power balance needs to be kept for the middle direct current bus of the back-to-back converter, and the constraint is that:
/>
the compensation power of the converters on the left side and the right side in the back-to-back converter needs to meet the capacity constraint of the equipment, and specifically comprises the following steps:
6.5 according to the negative sequence current real-time compensation objective function obtained in 6.3 and the back-to-back converter normal operation constraint condition obtained in 6.4, establishing a nonlinear programming model of an n-moment day optimization operation stage, and rapidly solving the model by utilizing a nonlinear optimization solving algorithm, such as a sequence quadratic programming algorithm, to obtain the back restReal-time active power compensation instruction of back current transformer at n timeAnd->Real-time reactive power compensation instruction->And->The instruction is issued to a real-time operation control system of the back-to-back converter;
step 7: acquiring ultra-short-term prediction data of traction load and photovoltaic output in the time k+2 to k+P+1 of a traction substation at the time k+1, establishing a model prediction control scheme at the time k+1 of the flexible traction substation, repeating the step 5, establishing a quadratic programming model of an intra-day optimization operation stage in the time k+2 to k+M+1, solving the model to obtain a charge and discharge power correction vector of an energy storage system at the time k+2, k+3, … and k+M+1, and transmitting correction quantity of a first time period (namely in the time k+2 to k+3) in the vector to a real-time operation control system of the energy storage system, so as to continuously roll forward for optimization;
Step 8: the correction quantity of the energy storage system in the k+1 to k+2 time obtained by the flexible traction substation k time model prediction control scheme is overlapped with the daily working plan value of the energy storage system in the k+1 to k+2 time to obtain the final working plan of the energy storage system in the k+1 to k+2 time; and (6) repeating the step (6) to solve the real-time optimization operation plan in the time k+1 to k+2, so as to obtain the photovoltaic real-time output power instruction in the time k+1 to k+2, the real-time active power and reactive power compensation instruction of the back-to-back converters and send the real-time active power and reactive power compensation instruction to the operation control system of each converter.
Therefore, as the daily operation time k increases, the steps 5, 6, 7 and 8 are repeated continuously, and the energy management of the flexible traction substation accessed by the photovoltaic and energy storage system can be completed all the day.
Example 2:
the structure of the flexible traction substation accessed by the photovoltaic and energy storage system is shown in fig. 1, and relevant parameters of part of equipment in the system are shown in table 1:
table 1 system device parameter settings
The method comprises the steps of taking a traditional traction power supply system as a reference group, taking a single time scale energy management scheme of solar power flow optimization scheduling of a flexible traction substation accessed by a photovoltaic and energy storage system as a comparison group, taking traction substation load prediction data obtained by a cyclic neural network prediction model as solar front prediction data, and obtaining solar ultra-short term prediction data by overlapping the solar front prediction data with normally distributed prediction errors. In a reference group of a traditional traction power supply system, a three-phase power grid supplies power for a train load during real-time operation; in a comparison group which only adopts daily trend optimization scheduling, the energy storage system operates according to the daily scheduling plan during real-time operation, the photovoltaic power generation system outputs according to the real-time maximum power point, the back-to-back converter performs negative sequence compensation by adopting the same method as the negative sequence current optimization compensation step in the invention, and the fluctuation of the train load is stabilized in real time by the three-phase power grid.
The comprehensive operation cost results of the traction substation obtained by simulation calculation of the schemes are shown in table 2:
TABLE 2 economic optimization results
According to the results of table 2, the flexible traction substation connected with the photovoltaic and energy storage system can effectively utilize the photovoltaic power generation resource and the regenerative braking energy, so that the running cost of the traction substation is reduced. Further, when the energy management scheme of the single time scale of day-ahead tide optimization scheduling is adopted, the electricity charge of the traction substation is reduced by 51.2%, the electricity charge of the required amount is reduced by 64.5%, and the total running cost is reduced by 48.9%. Under the multi-time-scale energy management scheme of the method, the electricity charge of the traction substation is reduced by 57.4%, the electricity charge of the required quantity is reduced by 60.2%, the total operation cost is reduced by 51.2%, and the economic operation capability of the traction substation is further improved.
In order to evaluate the effect of the multi-time scale energy management scheme, an average relative deviation of an evaluation index is defined, the index is used for evaluating the tracking effect of a working plan curve of PCC points after rolling optimization in the day on a day-ahead scheduling plan, and the smaller the value is, the better the tracking effect on the day-ahead scheduling plan is; conversely, a larger value indicates a poorer tracking effect on the day-ahead plan. The average relative deviation expression is as follows:
Wherein:optimizing a scheduling plan value for a daily trend of a traction substation PCC point at n moments in a real-time operation stage; />The actual values of the PCC points of the substation are pulled at the moment n in the real-time operation stage.
The technical index results related to the traction substation obtained by simulation calculation of each scheme are shown in table 3:
TABLE 3 technical index optimization results
As can be seen from the results of table 3, when the energy management scheme of the single time scale of day-ahead power flow optimization scheduling is adopted, errors between traction load operation data and photovoltaic output data and day-ahead predicted values are stabilized by the three-phase power grid only during real-time operation in the day, so that power fluctuation at the PCC point of the substation is larger, and the deviation degree from the day-ahead power flow optimization scheduling is also larger, as shown in fig. 4. After the multi-time-scale energy management scheme is adopted to correct the intra-day operation plan of the substation, adverse effects caused by traction load and photovoltaic output prediction errors are effectively reduced, the intra-day operation tracking capacity of the PCC point of the traction substation is obviously improved, and power fluctuation of the PCC point of the substation is low, as shown in FIG. 5.
In the aspect of negative sequence current compensation, when the energy management scheme of the single time scale of day-ahead tide optimization scheduling is adopted, the negative sequence current maximum value is reduced to 41.43A, and the negative sequence current 95% probability value is also reduced to 0.08A compared with a traditional traction power supply system due to the negative sequence compensation capability of the back-to-back converter. However, since the photovoltaic real-time output does not adopt a flexible output scheme, the negative sequence current compensation capability of the back-to-back converter is not fully exerted. Therefore, in the real-time operation stage, the photovoltaic flexible output scheme is considered, the maximum value of the negative sequence current of the primary side of the traction substation is further reduced to 30.82A, the 95% probability value of the negative sequence current is further reduced to 0.06A, and the negative sequence current compensation effect of the traction substation is better.
According to the invention, a direct current bus is led out from the middle direct current link of the back-to-back converter of the flexible traction substation to realize the connection of the photovoltaic power generation system and the energy storage system, and a multi-time scale energy management scheme of economic optimization scheduling before the day, intra-day error rolling correction and negative sequence current real-time compensation operation is used to realize the effective utilization of railway along-line photovoltaic power generation resources and train regeneration braking energy, reduce the comprehensive operation cost of the traction substation and promote economic operation capability; meanwhile, uncertainty of train traction load and photovoltaic output prediction is considered, and adverse effects of tracking of the traction substation on daily planned energy reduction caused by daily predicted data errors are reduced; the optimal compensation of the negative sequence current is further considered in the real-time operation stage, so that friendly interaction of the traction substation and the three-phase power grid is facilitated. The economic operation capacity of the traction substation is improved and the primary negative sequence current is reduced through the multi-time-scale energy management scheme, the operation scheme is provided for the access of the photovoltaic power generation system and the energy storage system in the electrified railway, and the engineering application foundation is provided for the future.
While the preferred embodiments of the present invention have been described in detail, the present invention is not limited to the above embodiments, and various changes may be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.
Many other changes and modifications may be made without departing from the spirit and scope of the invention. It is to be understood that the invention is not to be limited to the specific embodiments, but only by the scope of the appended claims.
Claims (10)
1. A method of energy management for a photovoltaic and energy storage system-accessed flexible traction substation, characterized by dividing a system energy management strategy into three time scales, the method comprising:
s1: in a day-ahead optimal scheduling stage, based on train traction load and photovoltaic output short-term prediction data, taking the lowest comprehensive operation cost of a traction substation as an objective function, constructing constraint conditions for ensuring normal operation of the traction substation, and establishing a mixed integer linear programming model of day-ahead power flow optimal scheduling;
s2: in the daily rolling optimization stage, taking the minimum power supply plan deviation of the traction substation as an objective function, and constructing constraint conditions for controlling the normal operation of the substation in a time domain to construct a model predictive control scheme of the flexible traction substation;
s3: in a real-time optimizing operation stage, a photovoltaic flexible output scheme is considered, a nonlinear optimizing model with the lowest negative sequence current of the primary side of the traction substation is established, a real-time power compensation instruction of the back-to-back converter is solved, and a real-time optimizing operation method of the flexible traction substation is established.
2. The method of energy management of a photovoltaic and energy storage system-accessed flexible traction substation of claim 1, wherein prior to said step S1, said method further comprises: the energy management method is divided into three time scales of day before, day in and real time.
3. The energy management method of the flexible traction substation, which is accessed by the photovoltaic and energy storage system, is characterized in that short-term prediction data of train loads and photovoltaic output of power supply arms at the left side and the right side of the traction substation in a dispatching day are obtained by adopting a traction load and photovoltaic prediction method;
the objective function of the mixed integer linear programming model established by the daily trend optimization scheduling is as follows:
wherein: c (C) DA To adjust the total running cost of the day; c G,b 、c G,s The electricity price of the traction substation and the electricity price of the return three-phase power grid are respectively; c D The price of the electricity charge is the required quantity; c Ess 、c PV The operation and maintenance costs of the energy storage and photovoltaic system are respectively;the power purchasing power and the returning power of the traction substation from the three-phase power grid at the moment t are respectively; p (P) Dem Is the maximum required power; />Respectively charging and discharging power of the energy storage system at the moment t; />The power output value of the photovoltaic power generation system at the moment t is; t is the dispatching time period number of the day-ahead tide optimization dispatching stage; Δt is the time scale of the day-ahead optimal scheduling phase.
4. The method for managing energy of a flexible traction substation to which a photovoltaic and energy storage system is connected according to claim 1, wherein the method for establishing constraint conditions of a day-ahead tide optimization scheduling stage based on short-term prediction data of train load and photovoltaic output according to a flexible traction substation model comprises the following steps: the power balance constraint of the substation, the power constraint of a primary side common connection point, namely a PCC point, the capacity constraint of the back-to-back converter, the charge and discharge power constraint of the energy storage system, the state of charge constraint of the energy storage medium and the maximum demand power constraint.
5. The energy management method for the flexible traction substation, which is accessed by the photovoltaic and energy storage system, is characterized in that after a mixed integer linear programming model of a day-ahead power flow optimization scheduling stage is established, the model is solved to obtain a power substation PCC point power plan, an energy storage system charge-discharge power plan and an energy storage medium charge state plan, namely the day-ahead power flow optimization scheduling of the flexible traction substation, which is accessed by the photovoltaic and energy storage system, is completed, and the scheduling plan is issued to a day-ahead rolling optimization operation stage in advance.
6. The energy management method for a flexible traction substation, which is accessed by a photovoltaic and energy storage system, according to claim 1, is characterized by establishing a model predictive control method for k time of the flexible traction substation in a rolling optimization operation stage in the day, and specifically comprising the following steps:
Selecting a vector formed by PCC point power at k moment of flexible traction substation, charging and discharging power of energy storage system and state of chargeIs a state vector; selecting increment of energy storage system output at k moment of flexible traction substation relative to planned value before day>Is a control vector; selecting increment constitution vector of ultra-short-term predicted power curve of total load and photovoltaic output of left and right power supply arm trains at k moment of flexible traction substation relative to day-ahead predicted curveIs a disturbance vector; selecting a vector formed by PCC point power at k moment of a flexible traction substation and state of charge of an energy storage system>For outputting vectors, establishing a prediction model of a flexible traction substation model prediction control method at the moment k:
wherein: η (eta) Ess The charge and discharge efficiency of the energy storage system is improved; Δk is the time scale of the intra-day scroll optimization phase.
7. The energy management method for a flexible traction substation, which is accessed by a photovoltaic and energy storage system, according to claim 1, is characterized in that ultra-short-term prediction data of traction load and photovoltaic output in a prediction time domain are obtained from k time instant to k+1 time instant, namely, the ultra-short-term prediction data of traction load and photovoltaic output in the prediction time domain are iterated step by step in the ultra-short-term prediction time domain by the medium prediction model, and an output vector matrix in the prediction time domain is constructed as follows:
Y k ＝[y k+1 ,y k+2 ,,y k+P ] T
Wherein: y is k+p (p=1, …, P) is an output vector of the prediction model, which predicts at k+p time and consists of the substation PCC power and the state of charge of the energy storage system;
based on the obtained traction load and photovoltaic output ultra-short-term prediction data, selecting k+1 time to k+M time of the flexible traction substation as a control time domain, wherein the control time domain is required to be smaller than or equal to a prediction time domain, namely M is less than or equal to P, and establishing an optimization target of a k time model prediction control method as follows:
wherein:for the tracking plan target matrix of k moment control time domain output vector, by every moment in time domain corresponding to power value ++f of PCC point in day-ahead plan>Energy storage state of charge-> Constructing; deltaU k For the control matrix in the k moment control time domain, the increment of the energy storage power at each moment in the time domain relative to the day-ahead plan is +.>Constructing; w, Q is a matrix of weight coefficients.
8. The method for energy management of a flexible traction substation to which a photovoltaic and energy storage system is connected according to claim 7, wherein the method for establishing constraint conditions under normal operating conditions in a control time domain of the flexible traction substation based on the ultra-short-term prediction data of the load and the photovoltaic output obtained in the foregoing model of the flexible traction substation comprises: power balance constraint of the substation, primary side public connection point power constraint, back-to-back converter capacity constraint, energy storage system charge and discharge power constraint, energy storage medium charge state constraint and maximum demand constraint;
According to the model predictive control method, a target function and a normal operation constraint condition of the obtained flexible traction substation in a control time domain are obtained, a quadratic programming model of an optimization operation stage in a day at a k moment is established, the quadratic programming model is solved, a charge and discharge power correction vector of the energy storage system at the k+1, k+2, … and k+M moments is obtained, and correction in the first time period, namely k+1 to k+2, in the vector is issued to the energy storage system real-time operation control system.
9. The energy management method for the flexible traction substation, which is accessed by the photovoltaic and energy storage system, according to claim 1, is characterized by comprising the following steps of:
the correction quantity of the energy storage system in the k-1 moment is obtained by a model predictive control method of the flexible traction substation at the k-1 moment, and the daily working plan value of the energy storage system in the k-1 moment is overlapped to obtain the final working plan of the energy storage system in the k-1 moment;
collecting the voltages of the power supply arms at the left side and the right side in real time in the time from k to k+1And->Load current of power supply arms at the left side and the right side>And->Photovoltaic array output voltage current value +. >And->Calculating active power of total load of trains with power supply arms on the left side and the right side +.>And->Reactive power and photovoltaic power generation>Judging whether the phenomenon of returning the PCC point power to the three-phase power grid exists at the current moment, and if the phenomenon of returning does not exist, operating the photovoltaic grid-connected converter in a maximum power point tracking mode; conversely, the photovoltaic power generation system adopts a limited power output mode, and the real-time output power of the photovoltaic power is expressed as follows:
wherein:and (5) obtaining the final working planning value of the energy storage system.
Based on the left power supply arm load and the right power supply arm load acquired in real time and the photovoltaic output power acquired after the control of the photovoltaic grid-connected converter, a negative sequence current real-time optimization compensation objective function is established as follows:
wherein: k (k) T A transformation ratio of the traction transformer;the total active power of the power supply arms at the alpha and beta phases at the n moments is respectively;the total reactive power of the power supply arms at the time of n is alpha and beta;
according to the flexible traction substation model and based on the obtained load real-time data and photovoltaic control output data, establishing constraint conditions under the normal operation condition of the back-to-back converter, wherein the constraint conditions comprise: power balance constraint of power supply arms on the left side and the right side, power balance constraint of a direct current bus and capacity constraint of a back-to-back converter;
According to the obtained negative sequence current real-time compensation objective function and the obtained back-to-back converter normal operation constraint condition, a nonlinear programming model of an n-moment day optimization operation stage is established, and the model is rapidly solved to obtain a real-time active power compensation instruction of the back-to-back converter at the n momentAnd->Real-time reactive power compensation instruction->And->And issues the instruction to a real-time operation control system of the back-to-back converter.
10. The method of claim 1, further comprising:
obtaining ultra-short-term prediction data of traction load and photovoltaic output in the time k+2 to the time k+P+1, establishing a model prediction control scheme of the flexible traction substation at the time k+1, repeatedly establishing a model prediction control method of the flexible traction substation at the time k in a rolling optimization operation stage in the day, establishing a quadratic programming model of the rolling optimization operation stage in the time k+2 to the time k+M+1, solving the model to obtain a charge and discharge power correction vector of the energy storage system in the time k+2, k+3, … and k+M+1, and transmitting correction quantity of the first time period, namely the time k+2 to k+3, in the vector to the real-time operation control system of the energy storage system, so that the energy storage system is continuously optimized in a rolling way;
The correction quantity of the energy storage system in the k+1 to k+2 moment is obtained by a model predictive control scheme of the k moment of the flexible traction substation, and the daily working plan value of the energy storage system in the k+1 to k+2 moment is overlapped to obtain the final working plan of the energy storage system in the k+1 to k+2 moment; repeating the real-time optimizing operation phase to construct a real-time optimizing operation method at the k+1 moment of the flexible traction substation, solving a real-time optimizing operation plan at the k+1 to k+2 moment, obtaining a photovoltaic real-time output power instruction at the k+1 to k+2 moment, a back-to-back converter real-time active power and reactive power compensation instruction, and issuing the photovoltaic real-time output power instruction, the back-to-back converter real-time active power and reactive power compensation instruction to an operation control system of each converter;
the construction is repeated continuously along with the increase of k, and the energy management method of the flexible traction substation for photovoltaic and energy storage system access is completed.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117039892A (en) * | 2023-10-08 | 2023-11-10 | 江苏省电力试验研究院有限公司 | Distribution area flexible interconnection system optimization scheduling method, system, equipment and storage medium |
| CN117810914A (en) * | 2024-02-27 | 2024-04-02 | 成都交大光芒科技股份有限公司 | Traction substation energy storage device running state prediction method and system |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117039892A (en) * | 2023-10-08 | 2023-11-10 | 江苏省电力试验研究院有限公司 | Distribution area flexible interconnection system optimization scheduling method, system, equipment and storage medium |
| CN117039892B (en) * | 2023-10-08 | 2024-01-19 | 江苏省电力试验研究院有限公司 | Distribution area flexible interconnection system optimization scheduling method, system, equipment and storage medium |
| CN117810914A (en) * | 2024-02-27 | 2024-04-02 | 成都交大光芒科技股份有限公司 | Traction substation energy storage device running state prediction method and system |
| CN117810914B (en) * | 2024-02-27 | 2024-05-03 | 成都交大光芒科技股份有限公司 | Traction substation energy storage device running state prediction method and system |
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