CN111106612A - Energy storage type charging pile participating power grid demand side response combined operation optimization model and solving algorithm - Google Patents

Energy storage type charging pile participating power grid demand side response combined operation optimization model and solving algorithm Download PDF

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CN111106612A
CN111106612A CN201811239625.8A CN201811239625A CN111106612A CN 111106612 A CN111106612 A CN 111106612A CN 201811239625 A CN201811239625 A CN 201811239625A CN 111106612 A CN111106612 A CN 111106612A
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energy storage
charging pile
storage type
type charging
power grid
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CN111106612B (en
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李鹏程
慈松
徐睿
范伟
周杨林
丛中笑
杨婧
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Guizhou Power Grid Co Ltd
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Electric Power Research Institute of Guizhou Power Grid Co Ltd
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    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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Abstract

The invention discloses a method for optimizing participation of an energy storage type charging pile in power grid demand side response joint operation, which is characterized by comprising the steps of initializing, establishing an energy storage type charging pile participation power grid demand side response joint operation optimization model, solving distributed energy joint optimization based on original-dual decomposition and the like. And establishing an energy storage type charging pile participation power grid demand side response combined operation optimization model which comprises an objective function of a maximized benefit function and constraint conditions such as energy storage type charging pile charging and discharging capacity constraint, capacity constraint and demand response electric quantity constraint. The distributed energy joint optimization solution based on the original-dual decomposition comprises the steps of constructing a Lagrangian function, constructing a Lagrangian dual function, applying a KKT condition, updating an iterative operator based on the original-dual decomposition and the like. The method provided by the invention can guide an energy storage type charging pile operator to adjust the power consumption according to the real-time power price change signal, improve the resource efficiency of the power, realize the maximization of social welfare, improve the economy of the energy storage type charging pile and fully exert the advantage of the energy storage type charging pile in the power grid for participating in the response of the demand side.

Description

Energy storage type charging pile participating power grid demand side response combined operation optimization model and solving algorithm
Technical Field
The invention belongs to the field of operation optimization of charging facilities, and relates to a method for optimizing the operation of an energy storage type charging pile participating in the response joint of the demand side of a power grid by combining with real-time electricity price incentive and comprehensively considering the influence of the performance of an energy storage system on the management compensation of the demand side.
Background
In recent years, electric automobiles in China are rapidly developed. The development of the electric automobile needs to invest in the construction of matched charging infrastructures including charging piles, so that the construction of the charging infrastructures of the electric automobile is greatly promoted, and the development of the electric automobile is an urgent task for accelerating the popularization and the application of the electric automobile. The mobile/distributed energy storage system is installed in the charging pile and the nearby charging pile in a matched mode, impact on a power grid caused by a random charging mode of an electric automobile can be relieved, and the energy storage type charging pile system plays an important role in future charging pile design.
To energy storage system and fill electric pile complex optimization operation problem, the existing research mainly focuses on how to utilize energy storage system to reduce electric automobile charging fluctuation. However, as a large number of electric vehicles are connected to the power grid under the condition of no adjustment and control, peak-to-peak superposition of a load curve of the power distribution network may occur, so that the peak-to-valley difference is further enlarged, the load risk of a line transformer is increased, and the effect and the economy of the research on the charging harmonic suppression on the optimal operation of the energy storage type charging pile and the power grid are not obvious enough.
At present, the cost of an energy storage system is high, and the investment cost of energy storage is difficult to recover in a mode of singly carrying out price arbitrage on a charging and discharging integrated energy storage charging pile. And energy storage formula fills electric pile and participates in power grid demand side response service and both can exert energy storage system power rapid adjustment's advantage, can obtain considerable income again, simultaneously, also can reduce the economic cost to energy storage system through the management of ordered charge-discharge.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the existing problems, the method for optimizing the response joint operation of the energy storage type charging pile participating in the power grid demand side is provided by combining the real-time electricity price incentive and comprehensively considering the influence of the performance of an energy storage system on the management compensation of the demand side.
The invention discloses a method for optimizing the participation of an energy storage type charging pile in power grid demand side response combined operation, which is characterized by comprising the following steps of:
step (1): initialization
Step (2): establishing energy storage type charging pile participation power grid demand side response combined operation optimization model
Step (2-1): the objective function is determined as follows:
Figure BSA0000172610710000021
represents: the energy storage type charging pile participates in a power grid demand side response joint operation optimization model, and a maximum benefit function is taken as a target.
Step (2-2): determining constraints
And (3): solving energy storage type charging pile participation power grid demand side response joint operation optimization model by adopting distributed energy joint optimization solving algorithm based on original-dual decomposition
Still further, the step (1) includes:
a) importing energy storage type charging pile parameters: and importing parameters such as energy storage capacity, maximum charge and discharge power, initial charge state and the like.
b) Importing power grid demand side response excitation power price information: and importing relevant excitation factors and electricity price information of the power grid for response excitation at the demand side.
Furthermore, in the step (2-1), in the objective function, the energy storage type charging pile benefit function is composed of weighted corresponding profit of the demand side and economic consumption of the energy storage type charging pile. The energy storage type charging pile operator determines power dispatching of participation of the energy storage type charging pile in power grid demand response according to change of demand response power price of the power grid operator
Figure BSA0000172610710000031
Charging and discharging scheduling of energy storage type charging pile
Figure BSA0000172610710000032
As shown in the following formula:
Figure BSA0000172610710000033
wherein the content of the first and second substances,
Figure BSA0000172610710000034
electric quantity for representing participation of energy storage type charging pile i in power grid demand response in t time slot
Figure BSA0000172610710000035
The gain in the amount of gain that is obtained,
Figure BSA0000172610710000036
and indicating the electric quantity of the energy storage type charging pile i participating in the response of the power grid demand side in the t time slot.
Figure BSA0000172610710000037
Representing cost-effectiveness of energy storage systems, mainly by charging/discharging current
Figure BSA0000172610710000038
And (6) determining.
Under V2G technical condition, electric current can flow between energy storage formula fills electric pile and electric wire netting bidirectionally, and energy storage formula fills electric pile and can purchase the electric quantity from the electric wire netting and be used for real-time electric automobile demand and energy storage system charge-discharge demand, and the electric quantity that electric pile participated in the electric wire netting demand response is filled to the energy storage formula promptly
Figure BSA0000172610710000039
Real-time charging demand by electric vehicle
Figure BSA00001726107100000310
Charging and discharging scheduling of energy storage type charging pile
Figure BSA00001726107100000311
Consists of the following components:
Figure BSA00001726107100000312
furthermore, the two contents included in the energy storage charging pile benefit function are specifically as follows:
a) energy storage type charging pile participation demand side response benefit
When the energy storage type charging pile participates in the power grid demand side response combined operation, the energy storage type charging pile is adjusted to participate in the power grid demand electric quantity according to the change of the power grid side demand price
Figure BSA00001726107100000313
And the demand response benefits obtained. According to the benefit that energy storage system responded in participating in demand side, the benefit that energy storage formula fills electric pile and participates in electric wire netting demand side response generally includes: incentive rewards based on participation demand response power and incentive rewards based on system benefits. The grid operator gives P the two demand response stimulitAnd mutThe unit electric quantity reward, the demand response income that fills electric pile operator and obtain promptly is as follows:
Figure BSA00001726107100000314
in the formula (I), the compound is shown in the specification,
Figure BSA00001726107100000315
show and fill electric pile average electric quantity demand in T time, show as:
Figure BSA00001726107100000316
b) energy storage economical loss of energy storage type charging pile
Considering the dynamic change of the State of charge (Soc) caused by the charging and discharging operations of the energy storage charging pile in the operation process, the Soc dynamic model can be expressed as:
Figure BSA0000172610710000041
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000048
represents the Soc state of the charging post i at time t of the battery,
Figure BSA0000172610710000042
the initial Soc state of the battery is shown, the unit of the initial Soc state is battery energy storage capacity (Ah), and T represents the time period of the combined operation of the energy storage system and the charging pile. Different charging/discharging operations of the energy storage system can generate economic expenses of different degrees for the energy storage type charging pile, and the expenses are mainly generated by two charging/discharging behavior indexes, namely charging/discharging depth and charging/discharging frequency. The energy storage economy loss can be expressed as:
Figure BSA0000172610710000043
in the formula, deltai,αiAnd gammaiAre all that the normal number weight value represents the influence of different charging/discharging behaviors on the economic loss of the battery,
Figure BSA0000172610710000044
representing the energy storage system maximum capacity.
Further, the constraints of the step (2-2) include:
a) energy storage type charging pile charge and discharge amount constraint
The constraint condition of the charging and discharging amount of the energy storage type charging pile in any unit time slot represents the electric quantity limit constraint in the charging/discharging process of the charging pile, and is shown as the following formula:
Figure BSA0000172610710000045
wherein the content of the first and second substances,
Figure BSA0000172610710000046
the maximum charging/discharging power of the charging pile.The formula represents the charge/discharge amount of any energy storage type charging pile in any time slot
Figure BSA0000172610710000047
The maximum charge/discharge capacity limit is satisfied and is limited within the rated charge/discharge capacity range.
b) Energy storage type charging pile capacity constraint
Because the energy storage formula fills electric pile has the restriction of certain capacity, energy storage system Soc value is too high or low will influence and fill the normal operation requirement of electric pile, for example, energy storage system Soc deviates from the median seriously, may lead to the energy storage because the electric quantity is too high or too low unable response fills electric pile system's instruction, and Soc is a continuous dynamic model, and its constraint condition can be expressed as:
Figure BSA0000172610710000051
according to the above formula, the capacity constraint of the energy storage system will charge/discharge the charging pile Ci tCreating an indirect effect.
c) Demand response power constraints
The electric quantity that electric pile participated in the power grid demand response should satisfy the maximum electric quantity restriction at the energy storage formula in arbitrary unit time slot, and its response electric quantity restraint is:
Figure BSA0000172610710000052
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000053
and the maximum electric quantity limit of the energy storage type charging pile i participating in demand response in the unit time slot t is shown.
Furthermore, in the step (3), a solution algorithm of distributed energy joint optimization based on the original-dual decomposition is adopted to solve the optimization model obtained in the step (2). Through obtaining the operation function of each charging pile energy management, the KKT condition is applied to realize the decomposition of the problem, so that each charging pile can be iteratively updated according to the operation state of the charging pile, and finally, the optimal solution is obtained. The solving algorithm is divided into the following four steps:
a) construction of Lagrangian functions
Constructing a Lagrangian function based on the optimization objective function as shown in the following formula:
Figure BSA0000172610710000054
where λ, v are lagrange multipliers greater than 0.
b) Constructing a Lagrangian dual function:
on the basis of the Lagrangian function constructed in the previous step, taking the dual form of the Lagrangian function to construct and obtain the Lagrangian dual function, wherein the Lagrangian dual function is shown as the following formula:
Figure BSA0000172610710000061
according to the dual theorem, g (lambda, v) is less than or equal to P on the feasible fields of lambda and v*And P is the optimal solution of the constraint of the original problem in the constraint limiting condition.
c) Applying KKT conditions
When the feasible domain of solving the original problem is satisfied, the feasible domain of the dual problem is as follows:
λ>0,v>0
the complementary relaxation amounts are:
Figure BSA0000172610710000062
Figure BSA0000172610710000063
because the optimization problem model is a convex function, the feasible solution is a convex set, and the solution obtained by applying the KKT condition is the solution of the original problem, which is a sufficient necessary condition. Therefore, the problem decomposition method can be applied to obtain the operator of each charging pile needing to be solved and updated.
d) Updating operators based on primitive-dual decomposition
According to the principle of original-dual decomposition, each energy storage charging pile is according to P collectedt、μtAfter the signal, the operation scheduling of the energy storage type charging pile is updated in a distributed mode according to the self limiting condition, and the updating operator is as follows:
Figure BSA0000172610710000064
Figure BSA0000172610710000065
Figure BSA0000172610710000066
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000067
representing the gradient of the function L.
No parameter is coupled between the charging piles in the solving process, so that the splitting and solving can be carried out. The complexity of the algorithm mainly depends on the scale of an applicable scene, is related to the total number N of the charging piles participating in the joint optimization operation, is also related to the iteration number k in the operation process of each algorithm, and is referred to as o (kN).
In conclusion, due to the adoption of the technical scheme, the energy storage type charging pile has the advantages that an energy storage type charging pile operator can be guided to adjust the power consumption according to the real-time power price change signal, the resource efficiency of the power is improved, the social welfare maximization is realized, the economy of the energy storage type charging pile is improved, the advantage of the energy storage type charging pile in participating in the response of a demand side in a power grid is fully exerted, and the healthy development of electric vehicles and energy storage industries is facilitated.
Drawings
Fig. 1 is a flowchart of a method for optimizing the joint operation of energy storage charging piles participating in the response of the demand side of a power grid.
Detailed Description
All of the features disclosed in this specification, or all of the steps in any method or process so disclosed, may be combined in any combination, except combinations of features and/or steps that are mutually exclusive.
Any feature disclosed in this specification may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
The energy storage type charging pile participating power grid demand side response combined operation optimization method provided by the invention is described in more detail below with reference to the accompanying drawings.
The invention discloses a method for optimizing the participation of an energy storage type charging pile in power grid demand side response combined operation, which is characterized by comprising the following steps of:
step (1): initialization
Step (2): establishing energy storage type charging pile participation power grid demand side response combined operation optimization model
Step (2-1): the objective function is determined as follows:
Figure BSA0000172610710000081
represents: the energy storage type charging pile participates in a power grid demand side response joint operation optimization model, and a maximum benefit function is taken as a target.
Step (2-2): determining constraints
And (3): and solving a power storage type charging pile participation power grid demand side response joint operation optimization model by adopting a distributed energy joint optimization solving algorithm based on original-dual decomposition.
Still further, the step (1) includes:
a) importing energy storage type charging pile parameters: and importing parameters such as energy storage capacity, maximum charge and discharge power, initial charge state and the like.
b) Importing power grid demand side response excitation power price information: and importing relevant excitation factors and electricity price information of the power grid for response excitation at the demand side.
Further, in the step (2-1) of the objective function, the energy storage type chargingThe pile benefit function is composed of weighted demand side corresponding income and energy storage type charging pile economical consumption. The energy storage type charging pile operator determines power dispatching of participation of the energy storage type charging pile in power grid demand response according to change of demand response power price of the power grid operator
Figure BSA0000172610710000082
Charging and discharging scheduling of energy storage type charging pile
Figure BSA0000172610710000083
As shown in the following formula:
Figure BSA0000172610710000084
wherein the content of the first and second substances,
Figure BSA0000172610710000085
electric quantity for representing participation of energy storage type charging pile i in power grid demand response in t time slot
Figure BSA0000172610710000086
The gain in the amount of gain that is obtained,
Figure BSA0000172610710000087
and indicating the electric quantity of the energy storage type charging pile i participating in the response of the power grid demand side in the t time slot.
Figure BSA0000172610710000088
Representing cost-effectiveness of energy storage systems, mainly by charging/discharging current
Figure BSA0000172610710000089
And (6) determining.
Under V2G technical condition, electric current can flow between energy storage formula fills electric pile and electric wire netting bidirectionally, and energy storage formula fills electric pile and can purchase the electric quantity from the electric wire netting and be used for real-time electric automobile demand and energy storage system charge-discharge demand, and the electric quantity that electric pile participated in the electric wire netting demand response is filled to the energy storage formula promptly
Figure BSA00001726107100000810
Real-time charging demand by electric vehicle
Figure BSA00001726107100000811
Charging and discharging scheduling of energy storage type charging pile
Figure BSA00001726107100000812
Consists of the following components:
Figure BSA0000172610710000091
furthermore, the two contents included in the energy storage charging pile benefit function are specifically as follows:
a) energy storage type charging pile participation demand side response benefit
When the energy storage type charging pile participates in the power grid demand side response combined operation, the energy storage type charging pile is adjusted to participate in the power grid demand electric quantity according to the change of the power grid side demand price
Figure BSA0000172610710000092
And the demand response benefits obtained. According to the benefit that energy storage system responded in participating in demand side, the benefit that energy storage formula fills electric pile and participates in electric wire netting demand side response generally includes: incentive rewards based on participation demand response power and incentive rewards based on system benefits. The grid operator gives P the two demand response stimulitAnd mutThe unit electric quantity reward, the demand response income that fills electric pile operator and obtain promptly is as follows:
Figure BSA0000172610710000093
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000094
show and fill electric pile average electric quantity demand in T time, show as:
Figure BSA0000172610710000095
b) energy storage economical loss of energy storage type charging pile
Considering the dynamic change of the State of charge (Soc) caused by the charging and discharging operations of the energy storage charging pile in the operation process, the Soc dynamic model can be expressed as:
Figure BSA0000172610710000096
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000097
represents the Soc state of the charging post i at time t of the battery,
Figure BSA0000172610710000098
the initial Soc state of the battery is shown, the unit of the initial Soc state is battery energy storage capacity (Ah), and T represents the time period of the combined operation of the energy storage system and the charging pile. Different charging/discharging operations of the energy storage system can generate economic expenses of different degrees for the energy storage type charging pile, and the expenses are mainly generated by two charging/discharging behavior indexes, namely charging/discharging depth and charging/discharging frequency. The energy storage economy loss can be expressed as:
Figure BSA0000172610710000099
in the formula, deltai,αiAnd gammaiAre all that the normal number weight value represents the influence of different charging/discharging behaviors on the economic loss of the battery,
Figure BSA0000172610710000101
representing the energy storage system maximum capacity.
Further, the constraints of the step (2-2) include:
a) energy storage type charging pile charge and discharge amount constraint
The constraint condition of the charging and discharging amount of the energy storage type charging pile in any unit time slot represents the electric quantity limit constraint in the charging/discharging process of the charging pile, and is shown as the following formula:
Figure BSA0000172610710000102
wherein the content of the first and second substances,
Figure BSA0000172610710000103
the maximum charging/discharging power of the charging pile. The formula represents the charge/discharge amount of any energy storage type charging pile in any time slot
Figure BSA0000172610710000104
The maximum charge/discharge capacity limit is satisfied and is limited within the rated charge/discharge capacity range.
b) Energy storage type charging pile capacity constraint
Because the energy storage formula fills electric pile has the restriction of certain capacity, energy storage system Soc value is too high or low will influence and fill the normal operation requirement of electric pile, for example, energy storage system Soc deviates from the median seriously, may lead to the energy storage because the electric quantity is too high or too low unable response fills electric pile system's instruction, and Soc is a continuous dynamic model, and its constraint condition can be expressed as:
Figure BSA0000172610710000105
according to the above formula, the capacity constraint of the energy storage system will charge/discharge the charging pile Ci tCreating an indirect effect.
c) Demand response power constraints
The electric quantity that electric pile participated in the power grid demand response should satisfy the maximum electric quantity restriction at the energy storage formula in arbitrary unit time slot, and its response electric quantity restraint is:
Figure BSA0000172610710000106
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000107
representing energy storage type charging pile i participating in demand response in t unit time slotAnd limiting the maximum electric quantity.
Furthermore, in the step (3), a solution algorithm of distributed energy joint optimization based on the original-dual decomposition is adopted to solve the optimization model obtained in the step (2). Through obtaining the operation function of each charging pile energy management, the KKT condition is applied to realize the decomposition of the problem, so that each charging pile can be iteratively updated according to the operation state of the charging pile, and finally, the optimal solution is obtained. The solving algorithm is divided into the following four steps:
a) construction of Lagrangian functions
Constructing a Lagrangian function based on the optimization objective function as shown in the following formula:
Figure BSA0000172610710000111
where λ, v are lagrange multipliers greater than 0.
b) Constructing a Lagrangian dual function:
on the basis of the Lagrangian function constructed in the previous step, taking the dual form of the Lagrangian function to construct and obtain the Lagrangian dual function, wherein the Lagrangian dual function is shown as the following formula:
Figure BSA0000172610710000112
according to the dual theorem, g (lambda, v) is less than or equal to P on the feasible fields of lambda and v*And P is the optimal solution of the constraint of the original problem in the constraint limiting condition.
c) Applying KKT conditions
When the feasible domain of solving the original problem is satisfied, the feasible domain of the dual problem is as follows:
λ>0,v>0
the complementary relaxation amounts are:
Figure BSA0000172610710000113
Figure BSA0000172610710000114
because the optimization problem model is a convex function, the feasible solution is a convex set, and the solution obtained by applying the KKT condition is the solution of the original problem, which is a sufficient necessary condition. Therefore, the problem decomposition method can be applied to obtain the operator of each charging pile needing to be solved and updated.
d) Updating operators based on primitive-dual decomposition
According to the principle of original-dual decomposition, each energy storage charging pile is according to P collectedt、μtAfter the signal, the operation scheduling of the energy storage type charging pile is updated in a distributed mode according to the self limiting condition, and the updating operator is as follows:
Figure BSA0000172610710000121
Figure BSA0000172610710000122
Figure BSA0000172610710000123
in the formula (I), the compound is shown in the specification,
Figure BSA0000172610710000124
representing the gradient of the function L.
No parameter is coupled between the charging piles in the solving process, so that the splitting and solving can be carried out. The complexity of the algorithm mainly depends on the scale of an applicable scene, is related to the total number N of the charging piles participating in the joint optimization operation, is also related to the iteration number k in the operation process of each algorithm, and is referred to as o (kN).
The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.

Claims (5)

1. A method for optimizing the joint operation of energy storage type charging piles participating in power grid demand side response is characterized by comprising the following steps:
step (1): initialization
Step (2): establishing energy storage type charging pile participation power grid demand side response combined operation optimization model
Step (2-1): the objective function is determined as follows:
Figure FSA0000172610700000011
represents: the energy storage type charging pile participates in a power grid demand side response joint operation optimization model, and a maximum benefit function is taken as a target.
Step (2-2): determining constraints
And (3): and solving a power storage type charging pile participation power grid demand side response joint operation optimization model by adopting a distributed energy joint optimization solving algorithm based on original-dual decomposition.
2. A distributed energy joint optimization solving algorithm based on original-dual decomposition is characterized in that: according to the algorithm, the operation function of energy management of each charging pile is obtained, and then the KKT condition is applied to realize the decomposition of the problem, so that each charging pile can be iteratively updated according to the operation state of the charging pile, and finally the optimal solution is obtained. The algorithm comprises the following steps:
a) construction of Lagrangian functions
Constructing a Lagrangian function based on the optimization objective function as shown in the following formula:
Figure FSA0000172610700000012
where λ, v are lagrange multipliers greater than 0.
b) Constructing a Lagrangian dual function:
on the basis of the Lagrangian function constructed in the previous step, taking the dual form of the Lagrangian function to construct and obtain the Lagrangian dual function, wherein the Lagrangian dual function is shown as the following formula:
Figure FSA0000172610700000021
according to the dual theorem, g (lambda, v) is less than or equal to P on the feasible fields of lambda and v*And P is the optimal solution of the constraint of the original problem in the constraint limiting condition.
c) Applying KKT conditions
When the feasible domain of solving the original problem is satisfied, the feasible domain of the dual problem is as follows:
λ>0,v>0
the complementary relaxation amounts are:
Figure FSA0000172610700000022
Figure FSA0000172610700000023
because the optimization problem model is a convex function, the feasible solution is a convex set, and the solution obtained by applying the KKT condition is the solution of the original problem, which is a sufficient necessary condition. Therefore, the problem decomposition method can be applied to obtain the operator of each charging pile needing to be solved and updated.
d) Updating operators based on primitive-dual decomposition
According to the principle of original-dual decomposition, each energy storage charging pile is according to P collectedt、μtAfter the signal, the operation scheduling of the energy storage type charging pile is updated in a distributed mode according to the self limiting condition, and the updating operator is as follows:
Figure FSA0000172610700000024
Figure FSA0000172610700000025
Figure FSA0000172610700000026
in the formula (I), the compound is shown in the specification,
Figure FSA0000172610700000027
representing the gradient of the function L.
No parameter is coupled between the charging piles in the solving process, so that the splitting and solving can be carried out. The complexity of the algorithm mainly depends on the scale of an applicable scene, is related to the total number N of the charging piles participating in the joint optimization operation, is also related to the iteration number k in the operation process of each algorithm, and is referred to as o (kN).
3. The method for participating in power grid demand side response joint operation optimization through the energy storage charging pile according to claim 1, wherein the step (1) comprises the following steps:
a) importing energy storage type charging pile parameters: and importing parameters such as energy storage capacity, maximum charge and discharge power, initial charge state and the like.
b) Importing power grid demand side response excitation power price information: and importing relevant excitation factors and electricity price information of the power grid for response excitation at the demand side.
4. The method for participating in power grid demand side response joint operation optimization through the energy storage type charging pile according to claim 1, wherein in the step (2-1) of the objective function, the energy storage type charging pile benefit function is composed of weighted demand side corresponding income and energy storage type charging pile economic consumption. The energy storage type charging pile operator determines power dispatching of participation of the energy storage type charging pile in power grid demand response according to change of demand response power price of the power grid operator
Figure FSA0000172610700000031
Charging and discharging scheduling of energy storage type charging pile
Figure FSA0000172610700000032
As shown in the following formula:
Figure FSA0000172610700000033
wherein the content of the first and second substances,
Figure FSA0000172610700000034
electric quantity for representing participation of energy storage type charging pile i in power grid demand response in t time slot
Figure FSA0000172610700000035
The gain in the amount of gain that is obtained,
Figure FSA0000172610700000036
and indicating the electric quantity of the energy storage type charging pile i participating in the response of the power grid demand side in the t time slot.
Figure FSA0000172610700000037
Representing cost-effectiveness of energy storage systems, mainly by charging/discharging current
Figure FSA0000172610700000038
And (6) determining.
Under V2G technical condition, electric current can flow between energy storage formula fills electric pile and electric wire netting bidirectionally, and energy storage formula fills electric pile and can purchase the electric quantity from the electric wire netting and be used for real-time electric automobile demand and energy storage system charge-discharge demand, and the electric quantity that electric pile participated in the electric wire netting demand response is filled to the energy storage formula promptly
Figure FSA0000172610700000039
Real-time charging demand by electric vehicle
Figure FSA00001726107000000310
Charging and discharging scheduling of energy storage type charging pile
Figure FSA00001726107000000311
Consists of the following components:
Figure FSA00001726107000000312
furthermore, the two contents included in the energy storage charging pile benefit function are specifically as follows:
a) energy storage type charging pile participation demand side response benefit
When the energy storage type charging pile participates in the power grid demand side response combined operation, the energy storage type charging pile is adjusted to participate in the power grid demand electric quantity according to the change of the power grid side demand price
Figure FSA0000172610700000041
And the demand response benefits obtained. According to the benefit that energy storage system responded in participating in demand side, the benefit that energy storage formula fills electric pile and participates in electric wire netting demand side response generally includes: incentive rewards based on participation demand response power and incentive rewards based on system benefits. The grid operator gives P the two demand response stimulitAnd mutThe unit electric quantity reward, the demand response income that fills electric pile operator and obtain promptly is as follows:
Figure FSA0000172610700000042
in the formula (I), the compound is shown in the specification,
Figure FSA0000172610700000043
show and fill electric pile average electric quantity demand in T time, show as:
Figure FSA0000172610700000044
b) energy storage economical loss of energy storage type charging pile
Considering the dynamic change of the State of charge (Soc) caused by the charging and discharging operations of the energy storage charging pile in the operation process, the Soc dynamic model can be expressed as:
Figure FSA0000172610700000045
in the formula (I), the compound is shown in the specification,
Figure FSA0000172610700000046
represents the Soc state of the charging post i at time t of the battery,
Figure FSA0000172610700000047
the initial Soc state of the battery is shown, the unit of the initial Soc state is battery energy storage capacity (Ah), and T represents the time period of the combined operation of the energy storage system and the charging pile. Different charging/discharging operations of the energy storage system can generate economic expenses of different degrees for the energy storage type charging pile, and the expenses are mainly generated by two charging/discharging behavior indexes, namely charging/discharging depth and charging/discharging frequency. The energy storage economy loss can be expressed as:
Figure FSA0000172610700000048
in the formula, deltai,αiAnd gammaiAre all that the normal number weight value represents the influence of different charging/discharging behaviors on the economic loss of the battery,
Figure FSA0000172610700000049
representing the energy storage system maximum capacity.
5. The method for participating in power grid demand side response joint operation optimization through the energy storage charging pile according to claim 1, wherein the constraint conditions of the step (2-2) comprise:
a) energy storage type charging pile charge and discharge amount constraint
The constraint condition of the charging and discharging amount of the energy storage type charging pile in any unit time slot represents the electric quantity limit constraint in the charging/discharging process of the charging pile, and is shown as the following formula:
Figure FSA0000172610700000051
wherein the content of the first and second substances,
Figure FSA0000172610700000052
for maximum charge/discharge work of charging pileAnd (4) rate. The formula represents the charge/discharge amount of any energy storage type charging pile in any time slot
Figure FSA0000172610700000053
The maximum charge/discharge capacity limit is satisfied and is limited within the rated charge/discharge capacity range.
b) Energy storage type charging pile capacity constraint
Because the energy storage formula fills electric pile has the restriction of certain capacity, energy storage system Soc value is too high or low will influence and fill the normal operation requirement of electric pile, for example, energy storage system Soc deviates from the median seriously, may lead to the energy storage because the electric quantity is too high or too low unable response fills electric pile system's instruction, and Soc is a continuous dynamic model, and its constraint condition can be expressed as:
Figure FSA0000172610700000054
according to the above formula, the capacity constraint of the energy storage system will charge/discharge the charging pile Ci tCreating an indirect effect.
c) Demand response power constraints
The electric quantity that electric pile participated in the power grid demand response should satisfy the maximum electric quantity restriction at the energy storage formula in arbitrary unit time slot, and its response electric quantity restraint is:
Figure FSA0000172610700000055
in the formula (I), the compound is shown in the specification,
Figure FSA0000172610700000056
and the maximum electric quantity limit of the energy storage type charging pile i participating in demand response in the unit time slot t is shown.
Further, in the step (3), the solution algorithm of the distributed energy joint optimization based on the original-dual decomposition according to claim 2 is adopted to solve the optimization model obtained in the step (2).
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111724080A (en) * 2020-06-29 2020-09-29 南京工程学院 Mobile charging pile group scheduling method considering battery pack health state balance
CN111738611A (en) * 2020-06-29 2020-10-02 南京工程学院 Mobile charging pile group intelligent scheduling method based on Sarsa algorithm
CN112636330A (en) * 2020-12-02 2021-04-09 上海交通大学 Comprehensive energy system peak regulation method based on user contribution behaviors

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104966127A (en) * 2015-06-03 2015-10-07 东南大学 Electric vehicle economic dispatching method based on demand response
CN106058904A (en) * 2016-06-30 2016-10-26 全球能源互联网研究院 Capacity matching method for energy storage type electric vehicle charging pile
CN106253315A (en) * 2016-08-02 2016-12-21 万马联合新能源投资有限公司 A kind of energy accumulation capacity configuration considering electric automobile charging station schedulability
CN106299511A (en) * 2016-08-02 2017-01-04 万马联合新能源投资有限公司 Electric automobile charging station energy storage capacity optimization method
CN106364344A (en) * 2016-09-19 2017-02-01 北京慧峰聚能科技有限公司 Energy management method of electric automobile charging demand side distributed system
CN106779487A (en) * 2017-01-17 2017-05-31 国网江西省电力公司电力科学研究院 A kind of virtual plant dynamic economic dispatch model based on prim al- dual interior point m ethod
US20170337646A1 (en) * 2016-05-19 2017-11-23 Hefei University Of Technology Charging and discharging scheduling method for electric vehicles in microgrid under time-of-use price
CN107689634A (en) * 2017-08-24 2018-02-13 国网新疆电力公司电力科学研究院 Demand-side two-way interaction control method based on energy storage type charging pile

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104966127A (en) * 2015-06-03 2015-10-07 东南大学 Electric vehicle economic dispatching method based on demand response
US20170337646A1 (en) * 2016-05-19 2017-11-23 Hefei University Of Technology Charging and discharging scheduling method for electric vehicles in microgrid under time-of-use price
CN106058904A (en) * 2016-06-30 2016-10-26 全球能源互联网研究院 Capacity matching method for energy storage type electric vehicle charging pile
CN106253315A (en) * 2016-08-02 2016-12-21 万马联合新能源投资有限公司 A kind of energy accumulation capacity configuration considering electric automobile charging station schedulability
CN106299511A (en) * 2016-08-02 2017-01-04 万马联合新能源投资有限公司 Electric automobile charging station energy storage capacity optimization method
CN106364344A (en) * 2016-09-19 2017-02-01 北京慧峰聚能科技有限公司 Energy management method of electric automobile charging demand side distributed system
CN106779487A (en) * 2017-01-17 2017-05-31 国网江西省电力公司电力科学研究院 A kind of virtual plant dynamic economic dispatch model based on prim al- dual interior point m ethod
CN107689634A (en) * 2017-08-24 2018-02-13 国网新疆电力公司电力科学研究院 Demand-side two-way interaction control method based on energy storage type charging pile

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
朱金卫等: "储能型电动汽车充电站研究进展", 《浙江电力》 *
李路遥: "含电动汽车和储能系统的微网能量优化管理", 《新型工业化》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111724080A (en) * 2020-06-29 2020-09-29 南京工程学院 Mobile charging pile group scheduling method considering battery pack health state balance
CN111738611A (en) * 2020-06-29 2020-10-02 南京工程学院 Mobile charging pile group intelligent scheduling method based on Sarsa algorithm
CN111738611B (en) * 2020-06-29 2024-04-26 南京工程学院 Intelligent scheduling method for mobile charging pile group based on Sarsa algorithm
CN112636330A (en) * 2020-12-02 2021-04-09 上海交通大学 Comprehensive energy system peak regulation method based on user contribution behaviors
CN112636330B (en) * 2020-12-02 2023-01-10 上海交通大学 Comprehensive energy system peak regulation method based on user contribution behaviors

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