CN111740411B - BSS-containing microgrid combined system optimization scheduling method considering backlog penalty mechanism - Google Patents

BSS-containing microgrid combined system optimization scheduling method considering backlog penalty mechanism Download PDF

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CN111740411B
CN111740411B CN202010576296.7A CN202010576296A CN111740411B CN 111740411 B CN111740411 B CN 111740411B CN 202010576296 A CN202010576296 A CN 202010576296A CN 111740411 B CN111740411 B CN 111740411B
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cost
battery
bss
period
backlog
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CN111740411A (en
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崔杨
刘柏岩
仲悟之
付小标
赵钰婷
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Northeast Electric Power University
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Northeast Dianli University
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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
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/64—Optimising energy costs, e.g. responding to electricity rates
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/80—Exchanging energy storage elements, e.g. removable batteries
    • 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
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • 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
    • 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]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/92—Energy efficient charging or discharging systems for batteries, ultracapacitors, supercapacitors or double-layer capacitors specially adapted for vehicles
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

The invention relates to an optimized scheduling method of a BSS-containing micro-grid combined system considering a backlog punishment mechanism, which is characterized by comprising the steps of establishing a grid-connectable micro-grid combined system containing BSS, carrying out preferential energy charging by comparing the power generation cost of MT, wind power and electricity purchased from a main grid, introducing the backlog punishment mechanism, reserving electric energy for an electric automobile by using a BSS battery pack as an energy storage system, punishment according to the completion condition of battery replacement service provided by BSS to the owner of the electric automobile, feeding back the battery replacement completion condition to the combined system, and making a battery charging and replacement plan according to the feedback of a user side. And finally, constructing a BSS-containing microgrid combined system optimization scheduling model considering a backlog penalty mechanism by taking the minimum sum of fan cost, MT cost, system standby cost, battery depreciation cost, backlog penalty cost and electricity purchasing cost of the combined system from the main network as a target. The method has the advantages of being scientific and reasonable, high in applicability, high in system energy utilization rate, low in operation cost and the like.

Description

BSS-containing microgrid combined system optimization scheduling method considering backlog penalty mechanism
Technical Field
The invention relates to the field of energy utilization, in particular to an optimal scheduling method of a BSS-containing micro-grid combined system considering a backlog punishment mechanism.
Background
The energy supply mode of the electric automobile can be divided into slow charging, fast charging and battery replacement modes, wherein the environment friendliness and the rapidness of the battery replacement mode enable the energy supply mode to become an important energy supply mode of the future electric automobile, and the energy supply mode becomes an important development mode. However, a feedback interaction manner between a Battery Swapping Station (BSS) operation strategy and a user side is always a research difficulty for scheduling of a microgrid combined system including a battery swapping station.
The micro-grid combined system comprising the BSS can select a cost optimal mode to charge the BSS empty battery according to the power generation cost of three modes of wind power, Micro Turbine (MT) and power grid electricity purchasing in the micro-grid. The BSS can store the charging energy in the microgrid in a power battery pack of the electric automobile, and the full batteries in the station are used for replacing the empty batteries of the electric automobile when the electric automobile drives into the BSS.
Disclosure of Invention
The basic concept of the invention is as follows: based on two aspects of improving the energy utilization rate and reducing the system power generation cost, a microgrid combined system power generation, BSS stored electric energy and backlog penalty mechanism is gradually introduced, a BSS-containing microgrid combined system model considering the backlog penalty mechanism is constructed, backlog penalty cost is added into an objective function, the electricity conversion completion degree is added into a constraint condition to serve as a quantitative index, and the effectiveness of the scheduling model provided by the invention on improving the energy utilization rate and improving the economic operation of the system is analyzed.
The technical problem to be solved by the invention is as follows: the optimal scheduling method of the BSS-containing micro-grid combined system is scientific and reasonable, high in applicability and good in effect, and can improve energy utilization efficiency and operation economy.
The technical scheme for solving the technical problem is as follows: a BSS-containing microgrid combined system optimization scheduling method considering a backlog punishment mechanism is characterized in that a grid-connected microgrid combined system containing BSS is established, power generation cost of MT, wind power and power purchasing from a main network is compared to carry out preferential energy charging, the backlog punishment mechanism is introduced, a BSS battery pack is used as an energy storage system to store electric energy for an electric automobile, punishment is carried out according to the completion condition of battery replacement service provided by BSS to an electric automobile owner, the battery replacement completion condition is fed back to the combined system, and a more optimal battery charging and replacing plan is made by the system according to user side feedback, and the method specifically comprises the following steps:
step one, constructing a backlog penalty mechanism model based on multi-cycle BSS inventory:
a multi-cycle battery inventory dynamic model:
the BSS provides a battery replacement service for the electric automobile in a full and empty mode, and the battery rack is used as a storage position of all power batteries of the electric automobile in the BSS and can be used as energy storage equipment to operate in a storage battery mode; therefore, the battery state in the battery rack is totally three: charging, full and waiting for charging; when the electric automobile drives into the BSS, the new battery and the old battery are exchanged, and the BSS puts the replaced old battery into a battery rack to be charged; the variation situation that the BSS stores the full battery under the multi-cycle is as the formula (1);
Nr,t+1＝Nr,t-Pv,t+Nc,t (1)
in the formula: n is a radical ofr,tAnd Nr,t+1The number of the full batteries in the BSS in the period t and the period t +1 respectively; pv,tThe number of vehicles driving into the BSS to change the battery in a t period; n is a radical ofc,tThe number of the batteries being charged in the BSS at the t period;
a backlog penalty mechanism model:
in order to deal with the uncertainty of arrival of the battery replacement load, an electric vehicle with a battery which cannot be replaced in time may exist; a backlog penalty mechanism is introduced;
when the electric automobile arrives at the BSS, the BSS preferentially replaces the full storage battery for the electric automobile; if the battery replacement requirement of the electric automobile is greater than the number of the fully charged batteries in the BSS in a certain period, delaying the next period when some automobiles cannot replace the batteries in time, and generating a overstock punishment cost; when the next period starts, the BSS preferentially replaces the power of the electric vehicle delayed in the previous period; at the moment, if the full-charged battery in the period meets the battery replacement requirements of the remaining vehicles in the period and the previous period, no overstock penalty cost is generated in the period; if not, the vehicle is superposed with the vehicle overstocked in the previous period to generate penalty cost;
step two, constructing an optimal scheduling model of the BSS-containing microgrid combined system:
an objective function:
scheduling model to federate System operating cost PsunMinimization as an objective function, including Fan cost C1(ii) a MT cost C2(ii) a System spare cost C3(ii) a Cost of battery depreciation C4(ii) a Backlog penalty cost C5(ii) a The combined system purchases electricity cost C from the main network6；
min Psum＝C1+C2+C3+C4+C5+C6 (2)
Due to the fluctuation and randomness of wind energy, the fan has loss in different degrees in the running process; therefore, the fan needs to be regularly maintained, and operation and maintenance cost is generated at the moment; meanwhile, in order to promote wind power consumption, wind abandon punishment cost is introduced, and the total cost of the fan is the sum of the operation and maintenance cost of the fan and the wind abandon punishment cost:
Figure GDA0003139407930000021
in the formula: t is the total cycle number; dwThe unit wind power operation and maintenance cost; pw,tThe fan transmits power to the charger when the period is t; q. q.swPunishing cost for unit wind abandon; qw,tAbandoning the air quantity in the period of t;
the starting-up cost of the MT can be generated during the operation, and the starting-up and stopping cost of the MT is low and is ignored; meanwhile, MT generates gas cost when burning gas; neglect of MT pollution emission is set;
Figure GDA0003139407930000022
in the formula: n is a radical ofmtThe number of MT; lambda [ alpha ]nIs MTnUnit boot cost; zn,tIs a unit state variable which is a 0-1 variable;
Figure GDA0003139407930000023
is MTnThe power value transmitted to the charger in the period t; alpha is alphanAnd betanIs MTnThe consumption coefficient of;
due to the randomness and the volatility of wind power output, the combined system is required to set a reserve capacity to maintain the stable operation of the system in an isolated network operation state; the calculation formula of the spare cost is as shown in formula (5):
Figure GDA0003139407930000031
in the formula: pb,tActual spare capacity of the system for t period; q. q.sbSpare cost for system unit; pbl,tIs the theoretical reserve capacity of the system in the period t;
Figure GDA0003139407930000032
is the lower limit value of the n-type MT output; smaxCharging an upper limit value for the storage battery; ssocThe remaining SOC of the battery when the battery is replaced for the electric automobile; setting the theoretical spare capacity needed by the system as R% of the predicted load, and using the MT to provide spare for the system; because MT has a lower output limit value, the actual reserve capacity of the t period system should be selected from the larger value of the theoretical reserve capacity and the MT lower output limit value;
one complete cycle period of the storage battery comprises a discharging half cycle period and a charging half cycle period; the cycle life of the storage battery refers to the number of charge and discharge cycles which can be carried out under the condition of keeping a certain output capacity, the cycle life of the storage battery is closely related to the working mode and the use intensity, and the depth of discharge (DOD) of the storage battery is negatively related to the cycle life in a discharge half cycle period; therefore, the service strength of the storage battery of the electric automobile in daily use determines the cycle life of the storage battery, and the depreciation cost of the storage battery is indirectly influenced; the relationship between the cycle life and the depth of discharge of the battery is expressed by equation (6):
Figure GDA0003139407930000033
in the formula: czjThe cost for single depreciation when the storage battery is used; cbatThe purchase cost for the storage battery; n is a radical ofxhThe number of cycle life; a is0、a1…anIs a discharge characteristic constant;
when the BSS delays the timely replacement of the battery of the electric automobile, overstocking penalty cost is generated, and the cost can be superposed for many times;
Figure GDA0003139407930000034
in the formula: k is a radical ofcfPunishment cost is unit backlog; gtThe number of the electric automobiles with the batteries which cannot be replaced on time in the t period;
the system electricity purchasing cost is generated only when the combined system is connected to the grid, and the electricity purchasing price of the system from the external power grid is the time-of-use electricity price;
Figure GDA0003139407930000041
in the formula: dbuy,tThe unit electricity purchasing cost; pbuy,tPurchasing electric quantity from the main network for the t period system;
constraint conditions:
the difference between the power flowing to a charger in the combined system and the battery replacement electric quantity of the electric automobile is equal to the difference between the front and back periods of the residual electric quantity in the storage battery pack;
Figure GDA0003139407930000042
in the formula: η is the power transmission efficiency; b istThe total electric quantity of the storage battery pack is t period;
the MT output power in the combined system must meet the upper and lower limit output constraints:
Figure GDA0003139407930000043
in the formula
Figure GDA0003139407930000044
The upper limit value of the output force of the nth type MT;
when the fan and the MT transmit power, the transmission tie line power must meet the upper and lower limit constraints:
Figure GDA0003139407930000045
in the formula: pline,max、Pline,minRespectively an upper limit value and a lower limit value of the transmission power of the tie line;
when the MT is exerting force, the climbing constraint of the unit must be met:
Figure GDA0003139407930000046
in the formula:
Figure GDA0003139407930000047
is the n-type MT climbing rate limit value;
in order to simplify the simulation model, one charger is only capable of charging one battery at the same time, and the number of the charged batteries is less than or equal to the number of the chargers at any moment; the number of the charged motors in the BSS is limited, and the charging power of the BSS to the storage battery is not more than the sum of the output of all chargers:
Figure GDA0003139407930000048
in the formula: k is a radical ofcThe number of chargers is; pcThe rated power of the charger;
the storage battery states in the storage battery pack are divided into three types: charging, full, waiting for charging, the number of which satisfies the following constraints:
Figure GDA0003139407930000049
in the formula: n is a radical ofw,tThe number of batteries waiting to be charged for t cycles; m is the total number of batteries in the BSS;
in order to enable the combined system to finish the current-day battery replacement target, the accumulated backlog number of the last period is zero, namely the battery of the backlog vehicle can be successfully replaced before the last period of the current day is finished although the vehicle backlog exists in the midway;
ST＝0 (15)
STthe vehicle is a vehicle which cannot be timely replaced in the T period.
The invention provides an optimized scheduling method of a combined system of a microgrid with BSS (base station system) considering a backlog penalty mechanism, which is characterized by firstly analyzing an operation mechanism of the combined system of the microgrid with grid-connectable power and a micro-combustion engine, secondly absorbing a charging energy source through a power battery pack of an electric vehicle to be used as an energy storage device, then introducing the backlog penalty mechanism, carrying out penalty according to the completion condition of providing a battery replacement service for an electric vehicle owner by the BSS, feeding back the battery replacement completion condition to the combined system, making a better battery replacement plan according to the feedback of a user side by the system, and finally constructing an optimized scheduling model of the combined system of the microgrid with BSS considering the backlog penalty mechanism by taking the sum of fan cost, MT cost, system standby cost, battery depreciation cost, backlog penalty cost and electricity purchasing cost of the combined system from a main network as a minimum target. The method has the advantages of being scientific and reasonable, strong in applicability, good in effect and the like, and can improve energy utilization efficiency and operation economy.
Drawings
FIG. 1: a multi-cycle battery inventory dynamic model schematic;
FIG. 2: a schematic view of a principle flow of a backlog punishment mechanism;
FIG. 3: the structure of the BSS-containing combined system is shown schematically;
FIG. 4: the output condition of each type of unit of the combined system is schematically shown after grid connection;
FIG. 5: a schematic diagram of the change of the battery replacement load of the combined system after grid connection;
FIG. 6: the system cost and the air curtailment rate are in a relationship with the number of full batteries.
Detailed Description
The following describes a BSS-included microgrid joint system optimal scheduling method considering a backlog penalty mechanism by using the accompanying drawings and embodiments.
The invention relates to an optimized scheduling method of a BSS-containing micro-grid combined system considering a backlog punishment mechanism, which is characterized in that a grid-connectable micro-grid combined system containing BSS is established, power generation cost of MT, wind power and electricity purchased from a main grid is compared to carry out preferential energy charging, the backlog punishment mechanism is introduced, the mechanism principle refers to a scheme shown in a figure 1 and a figure 2, a BSS battery pack is used as an energy storage system to store electric energy for an electric automobile, punishment is carried out according to the completion condition of battery replacement service provided by the BSS to an electric automobile owner, the battery replacement completion condition is fed back to the combined system, and a better battery charging and replacing plan is made by the system according to the feedback of a user side, and the method specifically comprises the following steps:
step one, constructing a backlog penalty mechanism model based on multi-cycle BSS inventory:
a multi-cycle battery inventory dynamic model:
the BSS provides a battery replacement service for the electric automobile in a full and empty mode, and the battery rack is used as a storage position of all power batteries of the electric automobile in the BSS and can be used as energy storage equipment to operate in a storage battery mode; therefore, the battery state in the battery rack is totally three: charging, full and waiting for charging; when the electric automobile drives into the BSS, the new battery and the old battery are exchanged, and the BSS puts the replaced old battery into a battery rack to be charged; the variation situation that the BSS stores the full battery under the multi-cycle is as the formula (1);
Nr,t+1＝Nr,t-Pv,t+Nc,t (1)
in the formula: n is a radical ofr,tAnd Nr,t+1The number of the full batteries in the BSS in the period t and the period t +1 respectively; pv,tThe number of vehicles driving into the BSS to change the battery in a t period; n is a radical ofc,tThe number of the batteries being charged in the BSS at the t period;
a backlog penalty mechanism model:
in order to deal with the uncertainty of arrival of the battery replacement load, an electric vehicle with a battery which cannot be replaced in time may exist; a backlog penalty mechanism is introduced;
when the electric automobile arrives at the BSS, the BSS preferentially replaces the full storage battery for the electric automobile; if the battery replacement requirement of the electric automobile is greater than the number of the fully charged batteries in the BSS in a certain period, delaying the next period when some automobiles cannot replace the batteries in time, and generating a overstock punishment cost; when the next period starts, the BSS preferentially replaces the power of the electric vehicle delayed in the previous period; at the moment, if the full-charged battery in the period meets the battery replacement requirements of the remaining vehicles in the period and the previous period, no overstock penalty cost is generated in the period; if not, the vehicle is superposed with the vehicle overstocked in the previous period to generate penalty cost;
step two, constructing an optimal scheduling model of the BSS-containing microgrid combined system:
② an objective function:
scheduling model to federate System operating cost PsunMinimization as an objective function, including Fan cost C1(ii) a MT cost C2(ii) a System spare cost C3(ii) a Cost of battery depreciation C4(ii) a Backlog penalty cost C5(ii) a The combined system purchases electricity cost C from the main network6；
min Psum＝C1+C2+C3+C4+C5+C6 (2)
Due to the fluctuation and randomness of wind energy, the fan has loss in different degrees in the running process; therefore, the fan needs to be regularly maintained, and operation and maintenance cost is generated at the moment; meanwhile, in order to promote wind power consumption, wind abandon punishment cost is introduced, and the total cost of the fan is the sum of the operation and maintenance cost of the fan and the wind abandon punishment cost:
Figure GDA0003139407930000061
in the formula: t is the total cycle number; dwThe unit wind power operation and maintenance cost; pw,tThe fan transmits power to the charger when the period is t; q. q.swPunishing cost for unit wind abandon; qw,tAbandoning the air quantity in the period of t;
the starting-up cost of the MT can be generated during the operation, and the starting-up and stopping cost of the MT is low and is ignored; meanwhile, MT generates gas cost when burning gas; neglect of MT pollution emission is set;
Figure GDA0003139407930000062
in the formula: n is a radical ofmtThe number of MT; lambda [ alpha ]nIs MTnUnit boot cost; zn,tIs a unit state variable which is a 0-1 variable;
Figure GDA0003139407930000071
is MTnThe power value transmitted to the charger in the period t; alpha is alphanAnd betanIs MTnThe consumption coefficient of;
due to the randomness and the volatility of wind power output, the combined system is required to set a reserve capacity to maintain the stable operation of the system in an isolated network operation state; the calculation formula of the spare cost is as shown in formula (5):
Figure GDA0003139407930000072
in the formula: pb,tActual spare capacity of the system for t period; q. q.sbSpare cost for system unit; pbl,tIs the theoretical reserve capacity of the system in the period t;
Figure GDA0003139407930000073
is the lower limit value of the n-type MT output; smaxCharging an upper limit value for the storage battery; ssocThe remaining SOC of the battery when the battery is replaced for the electric automobile; setting the theoretical spare capacity needed by the system as R% of the predicted load, and using the MT to provide spare for the system; because MT has a lower output limit value, the actual reserve capacity of the t period system should be selected from the larger value of the theoretical reserve capacity and the MT lower output limit value;
one complete cycle period of the storage battery comprises a discharging half cycle period and a charging half cycle period; the cycle life of the storage battery refers to the number of charge and discharge cycles which can be carried out under the condition of keeping a certain output capacity, the cycle life of the storage battery is closely related to the working mode and the use intensity, and the depth of discharge (DOD) of the storage battery is negatively related to the cycle life in a discharge half cycle period; therefore, the service strength of the storage battery of the electric automobile in daily use determines the cycle life of the storage battery, and the depreciation cost of the storage battery is indirectly influenced; the relationship between the cycle life and the depth of discharge of the battery is expressed by equation (6):
Figure GDA0003139407930000074
in the formula: czjThe cost for single depreciation when the storage battery is used; cbatThe purchase cost for the storage battery; n is a radical ofxhThe number of cycle life; a is0、a1…anIs a discharge characteristic constant;
when the BSS delays the timely replacement of the battery of the electric automobile, overstocking penalty cost is generated, and the cost can be superposed for many times;
Figure GDA0003139407930000075
in the formula: k is a radical ofcfPunishment cost is unit backlog; gtThe number of the electric automobiles with the batteries which cannot be replaced on time in the t period;
the system electricity purchasing cost is generated only when the combined system is connected to the grid, and the electricity purchasing price of the system from the external power grid is the time-of-use electricity price;
Figure GDA0003139407930000081
in the formula: dbuy,tThe unit electricity purchasing cost; pbuy,tPurchasing electric quantity from the main network for the t period system;
constraint conditions:
the difference between the power flowing to a charger in the combined system and the battery replacement electric quantity of the electric automobile is equal to the difference between the front and back periods of the residual electric quantity in the storage battery pack;
Figure GDA0003139407930000082
in the formula: η is the power transmission efficiency; b istThe total electric quantity of the storage battery pack is t period;
the MT output power in the combined system must meet the upper and lower limit output constraints:
Figure GDA0003139407930000083
in the formula
Figure GDA0003139407930000084
The upper limit value of the output force of the nth type MT;
when the fan and the MT transmit power, the transmission tie line power must meet the upper and lower limit constraints:
Figure GDA0003139407930000085
in the formula: pline,max、Pline,minRespectively an upper limit value and a lower limit value of the transmission power of the tie line;
when the MT is exerting force, the climbing constraint of the unit must be met:
Figure GDA0003139407930000086
in the formula:
Figure GDA0003139407930000087
is the n-type MT climbing rate limit value;
in order to simplify the simulation model, one charger is only capable of charging one battery at the same time, and the number of the charged batteries is less than or equal to the number of the chargers at any moment; the number of the charged motors in the BSS is limited, and the charging power of the BSS to the storage battery is not more than the sum of the output of all chargers:
Figure GDA0003139407930000088
in the formula: k is a radical ofcThe number of chargers is; pcThe rated power of the charger;
the storage battery states in the storage battery pack are divided into three types: charging, full, waiting for charging, the number of which satisfies the following constraints:
Figure GDA0003139407930000089
in the formula: n is a radical ofw,tThe number of batteries waiting to be charged for t cycles; m is the total number of batteries in the BSS;
in order to enable the combined system to finish the current-day battery replacement target, the accumulated backlog number of the last period is zero, namely the battery of the backlog vehicle can be successfully replaced before the last period of the current day is finished although the vehicle backlog exists in the midway;
ST＝0 (15)
STthe vehicle is a vehicle which cannot be timely replaced in the T period.
The specific embodiment is as follows: according to the unit coupling relationship shown in fig. 3, a 10-node microgrid system is adopted to construct an embodiment, and the calculation conditions of the embodiment are described as follows:
the scheduling period is 24 hours, and the unit scheduling time interval is 1 hour; the system comprises 1 fan with the capacity of 250kW and 3 micro gas turbines, wherein the rated capacities of the three micro gas turbines are MT 1-MT 3-100 kW and MT 2-80 kW respectively; wherein the MT3 is dedicated to providing spare capacity for the system; and dispatching 100 general electric vehicles in the day. The electricity price is 1.0 yuan/kW.h in the peak time period of 11:00-15:00, 19:00-21:00, 0.55 yuan/kW.h in the ordinary time period of 8:00-10:00, 16:00-18:00 and 22:00-23:00, and is 0.28 yuan/kW.h in the valley time period of 0:00-7: 00.
In order to comparatively analyze the effectiveness of the scheduling method provided by the invention on improving the economic operation of the system, two scheduling schemes are set as follows:
scheme 1: the combined system operates in an isolated network;
scheme 2: and (5) carrying out grid-connected operation on the combined system.
Under the above calculation conditions, the method of the present invention is applied to optimize the output of each energy in the system, and the scheduling result is as follows:
the output conditions of various types of units of the combined system after grid connection are shown in figure 4. Because the operation and maintenance cost of the fan is low and the wind abandonment penalty cost exists, the system firstly uses wind power output, but because the total number of the batteries in the BSS has an upper limit and the battery replacement vehicles in the initial stage of the dispatching day are fewer, the BSS can be quickly filled with the initial empty batteries, and the system can not utilize surplus wind power to generate the wind abandonment. After 3, along with the gradual increase of the battery replacement vehicles, the condition that the circulation difficulty of the empty-full battery in the BSS is relieved, and simultaneously, along with the reduction of the wind power generation power, the wind power can be completely consumed. After 6, the system starts to use other ways to supply energy only by using wind power, wherein the energy supply is not enough to supply BSS to maintain the charging and replacing service. At this time, the electricity price is higher than the unit gas cost of MT, but the MT starting cost still leads the system to preferentially purchase electricity from the power grid under certain power limit. When the electricity price flat period is reached, the unit integrated power generation cost of the MT1 and the MT2 is lower than that of the electricity price in the flat period, the MT power supply is preferentially used by the system, and when the 16-point MT is fully generated, less electricity purchasing power is generated. After 20 o 'clock, the battery replacement vehicle is gradually reduced, meanwhile, the system gradually reduces the output to maintain the same initial and final state, the output of the MT2 is firstly reduced to zero, and when 24 o' clock, the output of the MT1 is reduced slightly at the same time.
Fig. 5 shows a change curve of the power conversion load of the combined system after grid connection. Before a backlog punishment mechanism is added, the number of full batteries of the system is less than the battery replacement load at 20 points due to the limited number of system chargers. After a backlog punishment mechanism is added, the system generates two backlog times at 20 points and 21 points respectively, so that the electric vehicle which is not successfully changed in power at 20 points moves backwards for two periods, and the system can successfully complete power change.
The system cost and wind curtailment rate versus the number of full batteries are shown in fig. 6. When other conditions are fixed, the total operation cost and the air curtailment rate of the combined system are positively correlated with the initial full battery number in the BSS. It can be known from the analysis of 3.2 sections that when the initial number of batteries is 13, the system cannot fully utilize wind power at 1-3 points, resulting in wind abandon. When the number of the initially full batteries is less than 13, the electric quantity shortage of the BSS battery pack is increased, the system can more fully utilize wind power to charge the empty batteries, and the wind power consumption is improved; on the contrary, when the number of full batteries is more than 13, the storage battery is already fully charged in advance, so that the wind abandoning rate is increased, and finally, additional wind abandoning cost is generated, so that the total cost is gradually increased.
Table 1 lists the detailed operating costs (dollars) for the two scheduling schemes.
TABLE 1 detailed operating costs for each protocol
Figure GDA0003139407930000101
As can be seen from table 1, the scheduling method provided by the present invention increases system stability and power conversion flexibility, so that the solution two saves standby cost and increases electricity purchasing cost compared with the solution one, and the example result shows that the total cost of the solution two is reduced by 514.9 yuan, i.e. 10.3%, and the superiority of BSS participating in grid connection is verified.
In addition, the backlog punishment mechanism provided by the invention can translate the battery replacement time of the vehicle which is not successfully replaced, and effectively optimize the battery replacement load curve.
The embodiments of the present invention have been described in order to explain the present invention rather than to limit the scope of the claims, and it is intended that all such modifications and variations that fall within the true spirit and scope of the invention are possible and within the scope of the invention.

Claims (1)

1. A BSS-containing microgrid combined system optimization scheduling method considering a backlog punishment mechanism is characterized in that a grid-connected microgrid combined system containing BSS is established, power generation cost of MT, wind power and power purchasing from a main network is compared to carry out preferential energy charging, the backlog punishment mechanism is introduced, a BSS battery pack is used as an energy storage system to store electric energy for an electric automobile, punishment is carried out according to the completion condition of battery replacement service provided by BSS to an electric automobile owner, the battery replacement completion condition is fed back to the combined system, and a more optimal battery charging and replacing plan is made by the system according to user side feedback, and the method specifically comprises the following steps:
step one, constructing a backlog penalty mechanism model based on multi-cycle BSS inventory:
a multi-cycle battery inventory dynamic model:
the BSS provides a battery replacement service for the electric automobile in a full and empty mode, and the battery rack is used as a storage position of all power batteries of the electric automobile in the BSS and can be used as energy storage equipment to operate in a storage battery mode; therefore, the battery state in the battery rack is totally three: charging, full and waiting for charging; when the electric automobile drives into the BSS, the new battery and the old battery are exchanged, and the BSS puts the replaced old battery into a battery rack to be charged; the variation situation that the BSS stores the full battery under the multi-cycle is as the formula (1);
Nr,t+1＝Nr,t-Pv,t+Nc,t (1)
in the formula: n is a radical ofr,tAnd Nr,t+1The number of the full batteries in the BSS in the period t and the period t +1 respectively; pv,tThe number of vehicles driving into the BSS to change the battery in a t period; n is a radical ofc,tThe number of the batteries being charged in the BSS at the t period;
a backlog penalty mechanism model:
in order to deal with the uncertainty of arrival of the battery replacement load, an electric vehicle with a battery which cannot be replaced in time may exist; a backlog penalty mechanism is introduced;
when the electric automobile arrives at the BSS, the BSS preferentially replaces the full storage battery for the electric automobile; if the battery replacement requirement of the electric automobile is greater than the number of the fully charged batteries in the BSS in a certain period, delaying the next period when some automobiles cannot replace the batteries in time, and generating a overstock punishment cost; when the next period starts, the BSS preferentially replaces the power of the electric vehicle delayed in the previous period; at the moment, if the full-charged battery in the period meets the battery replacement requirements of the remaining vehicles in the period and the previous period, no overstock penalty cost is generated in the period; if not, the vehicle is superposed with the vehicle overstocked in the previous period to generate penalty cost;
step two, constructing an optimal scheduling model of the BSS-containing microgrid combined system:
an objective function:
scheduling model to federate System operating cost PsunMinimization as an objective function, including Fan cost C1(ii) a MT cost C2(ii) a System spare cost C3(ii) a Cost of battery depreciation C4(ii) a Backlog penalty cost C5(ii) a The combined system purchases electricity cost C from the main network6；
minPsum＝C1+C2+C3+C4+C5+C6 (2)
Due to the fluctuation and randomness of wind energy, the fan has loss in different degrees in the running process; therefore, the fan needs to be regularly maintained, and operation and maintenance cost is generated at the moment; meanwhile, in order to promote wind power consumption, wind abandon punishment cost is introduced, and the total cost of the fan is the sum of the operation and maintenance cost of the fan and the wind abandon punishment cost:
Figure FDA0003139407920000021
in the formula: t is the total cycle number; dwIs a unit wind power systemMaintaining the cost; pw,tThe fan transmits power to the charger when the period is t; q. q.swPunishing cost for unit wind abandon; qw,tAbandoning the air quantity in the period of t;
the starting-up cost of the MT can be generated during the operation, and the starting-up and stopping cost of the MT is low and is ignored; meanwhile, MT generates gas cost when burning gas; neglect of MT pollution emission is set;
Figure FDA0003139407920000022
in the formula: n is a radical ofmtThe number of MT; lambda [ alpha ]nIs MTnUnit boot cost; zn,tIs a unit state variable which is a 0-1 variable;
Figure FDA0003139407920000023
is MTnThe power value transmitted to the charger in the period t; alpha is alphanAnd betanIs MTnThe consumption coefficient of;
due to the randomness and the volatility of wind power output, the combined system is required to set a reserve capacity to maintain the stable operation of the system in an isolated network operation state; the calculation formula of the spare cost is as shown in formula (5):
Figure FDA0003139407920000024
in the formula: pb,tActual spare capacity of the system for t period; q. q.sbSpare cost for system unit; pbl,tIs the theoretical reserve capacity of the system in the period t;
Figure FDA0003139407920000025
is the lower limit value of the n-type MT output; smaxCharging an upper limit value for the storage battery; ssocThe remaining SOC of the battery when the battery is replaced for the electric automobile; setting the theoretical spare capacity needed by the system as R% of the predicted load, and using the MT to provide spare for the system; the T period system is real because MT has a lower limit value of outputThe larger value of the theoretical reserve capacity and the MT output lower limit is selected as the actual reserve capacity;
one complete cycle period of the storage battery comprises a discharging half cycle period and a charging half cycle period; the cycle life of the storage battery refers to the number of charge and discharge cycles which can be carried out under the condition of keeping a certain output capacity, the cycle life of the storage battery is closely related to the working mode and the use intensity, and the depth of discharge (DOD) of the storage battery is negatively related to the cycle life in a discharge half cycle period; therefore, the service strength of the storage battery of the electric automobile in daily use determines the cycle life of the storage battery, and the depreciation cost of the storage battery is indirectly influenced; the relationship between the cycle life and the depth of discharge of the battery is expressed by equation (6):
Figure FDA0003139407920000031
in the formula: czjThe cost for single depreciation when the storage battery is used; cbatThe purchase cost for the storage battery; n is a radical ofxhThe number of cycle life; a is0、a1…anIs a discharge characteristic constant;
when the BSS delays the timely replacement of the battery of the electric automobile, overstocking penalty cost is generated, and the cost can be superposed for many times;
Figure FDA0003139407920000032
in the formula: k is a radical ofcfPunishment cost is unit backlog; gtThe number of the electric automobiles with the batteries which cannot be replaced on time in the t period;
the system electricity purchasing cost is generated only when the combined system is connected to the grid, and the electricity purchasing price of the system from the external power grid is the time-of-use electricity price;
Figure FDA0003139407920000033
in the formula: dbuy,tThe unit electricity purchasing cost; pbuy,tPurchasing electric quantity from the main network for the t period system;
constraint conditions:
the difference between the power flowing to a charger in the combined system and the battery replacement electric quantity of the electric automobile is equal to the difference between the front and back periods of the residual electric quantity in the storage battery pack;
Figure FDA0003139407920000034
in the formula: η is the power transmission efficiency; b istThe total electric quantity of the storage battery pack is t period;
the MT output power in the combined system must meet the upper and lower limit output constraints:
Figure FDA0003139407920000035
in the formula
Figure FDA0003139407920000036
The upper limit value of the output force of the nth type MT;
when the fan and the MT transmit power, the transmission tie line power must meet the upper and lower limit constraints:
Figure FDA0003139407920000037
in the formula: pline,max、Pline,minRespectively an upper limit value and a lower limit value of the transmission power of the tie line;
when the MT is exerting force, the climbing constraint of the unit must be met:
Figure FDA0003139407920000038
in the formula:
Figure FDA0003139407920000041
is the n-type MT climbing rate limit value;
in order to simplify the simulation model, one charger is only capable of charging one battery at the same time, and the number of the charged batteries is less than or equal to the number of the chargers at any moment; the number of the charged motors in the BSS is limited, and the charging power of the BSS to the storage battery is not more than the sum of the output of all chargers:
Figure FDA0003139407920000042
in the formula: k is a radical ofcThe number of chargers is; pcThe rated power of the charger;
the storage battery states in the storage battery pack are divided into three types: charging, full, waiting for charging, the number of which satisfies the following constraints:
Figure FDA0003139407920000043
in the formula: n is a radical ofw,tThe number of batteries waiting to be charged for t cycles; m is the total number of batteries in the BSS;
in order to enable the combined system to finish the current-day battery replacement target, the accumulated backlog number of the last period is zero, namely the battery of the backlog vehicle can be successfully replaced before the last period of the current day is finished although the vehicle backlog exists in the midway;
ST＝0 (15)
STthe vehicle is a vehicle which cannot be timely replaced in the T period.
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