CN114123260B - Renewable energy-oriented multi-energy micro-grid shared energy storage control method and system - Google Patents

Renewable energy-oriented multi-energy micro-grid shared energy storage control method and system Download PDF

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CN114123260B
CN114123260B CN202111352087.5A CN202111352087A CN114123260B CN 114123260 B CN114123260 B CN 114123260B CN 202111352087 A CN202111352087 A CN 202111352087A CN 114123260 B CN114123260 B CN 114123260B
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肖江文
曹文志
刘骁康
王燕舞
崔世常
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Huazhong University of Science and Technology
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Abstract

The invention discloses a renewable energy source-oriented multi-energy source micro-grid shared energy storage control method and system, and belongs to the field of new energy source consumption. The method comprises the steps of minimizing the total energy cost of all multi-energy micro-grids and hybrid energy storage systems participating in shared energy storage as an objective function; taking the energy flow between the micro-grid and the hybrid energy storage system as a decision variable; taking the electric quantity and the natural gas quantity purchased from the outside of the micro-grid and the energy flow in the single micro-grid as decision variables, converting the energy storage loss cost of the hybrid energy storage system, the charge and discharge speed of the hybrid energy storage system and the thermoelectric conversion of the hybrid energy storage system into the decision variables, and constructing constraint conditions for the decision variables to construct a hybrid energy storage system shared energy storage optimization control model; and solving the shared energy storage optimization control model of the hybrid energy storage system by adopting distributed optimization to obtain a control scheme of sharing a single hybrid energy storage system by a plurality of micro-grids.

Description

Renewable energy-oriented multi-energy micro-grid shared energy storage control method and system
Technical Field
The invention belongs to the field of renewable energy source digestion in an electric power system, and particularly relates to a multi-energy source micro-grid sharing energy storage control method and system for distributed renewable energy sources.
Background
Due to the increasing tension of conventional fossil energy, renewable energy has begun to be widely focused and developed, and various micro-grids with renewable energy generation have begun to rapidly develop in addition to large-scale renewable energy access to the grid. Renewable energy has the characteristics of intermittence and randomness, and challenges are presented to the dispatching work of the power grid; the grid connection of renewable energy sources has very large influence on the voltage and frequency of a large power grid, and the electric energy quality of the large power grid is seriously influenced; due to the imperfect electric power market, the utilization rate of renewable energy sources is not improved, and the waste rate is higher.
The most straightforward and reliable way to promote new energy consumption is to store the excess renewable energy with an energy storage battery for discharge at a later time for power consumption. But the investment cost of the energy storage battery of a single micro-grid equipment is high, so that the mode of adopting public energy storage is more economical. To further reduce energy storage costs, the combined multi-energy microgrid has thermal load and heat generation capacity, so it is more economical to add a common large thermal energy storage device. The thermal energy storage device has lower cost relative to the energy storage battery and larger capacity, and can avoid the condition that renewable energy power generation cannot be consumed due to the limitation of the capacity of the energy storage battery. Therefore, the public thermoelectric energy storage system is hopeful to become one of important control means for new energy consumption.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a renewable energy-oriented multi-energy micro-grid shared energy storage control method and system, which aim to solve the problems of energy storage and energy sharing of a renewable energy-oriented multi-energy micro-grid, and improve new energy consumption of renewable energy producers and consumers so as to reduce dependence on external energy sources such as power grids, natural gas and the like.
In order to achieve the above purpose, the present invention provides a renewable energy source-oriented multi-energy source micro-grid sharing energy storage control method, which comprises the following steps:
s1, taking the total cost of a micro-grid cluster and a hybrid energy storage system as a first objective function, taking the electric quantity and the natural gas quantity purchased from the outside of the micro-grid, the energy flow inside a single micro-grid, the energy storage loss cost of the hybrid energy storage system, the charge and discharge speed of the hybrid energy storage system, the thermoelectric conversion of the hybrid energy storage system, the direct energy flow of the micro-grid and the hybrid energy storage system as first decision variables, and constructing constraint conditions for each first decision variable so as to construct a multi-energy micro-grid shared energy storage control model comprising the first decision variables, the first objective function and the constraint conditions;
s2, solving a constructed multi-energy micro-grid shared energy storage control model by adopting a distributed optimization method;
s3, adopting a Nash equilibrium strategy, after obtaining the optimal solution in the step S2, maximizing the product of the net benefits of all the micro-grids and the hybrid energy storage system to be a second objective function, and calculating the transaction amount of each micro-grid and the hybrid energy storage system by taking the transaction amount of each micro-grid and the hybrid energy storage system as a second decision variable to obtain a control scheme of sharing multiple energy storage by multiple micro-grids.
Further, the first objective function is expressed as:
s.t.x n ∈X n ，y∈Y
wherein x is n Representing the decision variable of the micro-grid n, X n Representing the decision variable x n Y represents a hybrid energy storage system decision variable, Y represents a hybrid energy storage system decision variable constraint set, C n (x n ) Representing the cost of the micro grid n, C 0 (y) represents the running cost of the hybrid energy storage system and N represents the number of micro-grids.
Further, the cost of the micro grid n is expressed as:
wherein, representing the cost of the micro grid n purchasing power from the main grid at time t,representing the cost of the micro grid n to purchase natural gas at time t,/->And g n，t Representing the electric power and the natural gas volume purchased by the micro grid n from the main grid at time t, respectively,/->And gamma gas Representing the price of the electricity purchase and the price of the natural gas purchase, respectively.
Further, the running cost of the hybrid energy storage system is expressed as:
wherein, and->Operating costs of the energy storage battery and the heat storage device, respectively, < >>And->Respectively representing the charge power and the discharge power of the energy storage battery, < >>And->The charging power and the discharging power of the heat storage device are respectively represented.
Further, decision variable x n Is represented as follows:
decision variable x n Is a constraint set X of (1) n The expression is as follows:
wherein, and g n，t Representing the electric power and the natural gas volume purchased by the micro grid n from the main grid at time t, respectively,/->And->Representing natural gas for micro-grid gas turbines and gas boilers, respectively, < >>For the heat production of a gas turbine, +.>For the heat production efficiency of the gas turbine, L is the heating value of the natural gas, < >>For the power production of a gas turbine, +.>For the power generation efficiency of a gas turbine, +.>And->Respectively representing the heat production amount and the electricity production efficiency of the gas boiler, < ->Andrespectively representing the refrigerating capacity, refrigerating efficiency and consumed heat of the absorption refrigerator, +.>And->Respectively representing the refrigerating capacity, refrigerating efficiency and consumed electric quantity of the electric refrigerator, +.>Renewable energy generation capacity of a surface micro-grid, < -> And->Respectively representing the electric, thermal and cold loads of the micro-grid, < ->And->Respectively represents the wasted electric energy and heat energy of the micro-grid due to incapacitation, and the micro-grid is in a +.>And->The method comprises the steps of respectively representing electric energy and heat energy of a micro-grid and a hybrid energy storage system in a transaction mode, and representing that the micro-grid purchases energy from the hybrid energy storage system when the value is positive, and representing that the micro-grid sells the energy to the hybrid energy storage system when the value is negative;
the decision variable y is expressed as follows:
the constraint set Y of the decision variable Y is expressed as follows:
wherein S is t Indicating the energy level of the energy storage battery at time t,and->Respectively representing the charge and discharge efficiency of the energy storage battery, +.>And->Respectively represent the charge and discharge power of the energy storage battery, S min And S is max Respectively representing the lower limit and the upper limit of the energy level of the energy storage battery, < >>And->Respectively represent the maximum power of charging and discharging of the energy storage battery, H t Indicating the energy level of the heat storage system at time t, < >>And->Respectively represent the charging of the heat storage systemHeat release efficiency, < >>And->Respectively represent the charge and discharge power of the energy storage battery, H min And H max Representing the lower and upper limit, respectively, of the energy level of the heat storage system,/->And->Maximum power of heat storage system for heat charging and heat discharging, respectively,/->η eh And->Indicating the heat generation amount, heat generation efficiency and power consumption of the electric boiler,/->And->Representing the sum of electric energy or heat energy respectively traded by the hybrid energy storage system and the micro-grid, and if the sum is negative, representing that the hybrid energy storage system integrally purchases energy from the micro-grid, regularly representing that the hybrid energy storage system integrally sells energy to the micro-grid.
Further, step S2 includes the steps of:
s21, introducing auxiliary variablesAnd->Will restrict the set X n In (a) and (b)Coupling constraints
Decoupling is a pairwise coupling constraint->And independent constraint->
Introducing auxiliary variablesAnd->Coupling constraint in constraint set Y +.>Decoupling is a pairwise coupling constraint->And independent constraint->
The multi-energy micro-grid shared energy storage control model is converted into:
wherein lambda is n，t Andrepresenting the pair multiplier of the corresponding constraint;
s22, constructing the following Lagrangian function based on the converted objective function:
s.t.x n ∈X n ，y∈Y，θ∈Z
wherein μ and v represent given penalty parameters, q n And r is an auxiliary variable which is used as a reference,andthe method respectively represents the amount of energy purchased by the micro-grid from the hybrid energy storage system and the amount of energy sold by the hybrid energy storage system to the micro-grid, and Z is +.>And->
S23, solving the Lagrangian function for all decision variables through collaborative distributed iteration of an alternate direction multiplier method, so that an optimal solution is obtained.
Further, in step S22, when the lagrangian function is solved by using the alternate direction multiplier method, the current iteration number is represented by k, and in each iteration, the following steps are required to be executed:
(1) Updating decision variables of microgrid n
Wherein the method comprises the steps ofIs x n Is a sub-vector of (2);
(2) Updating decision variables of a hybrid energy storage system
Wherein e sh Is a sub-vector of y;
(3) Updating auxiliary variables
(4) Updating lagrangian multiplier lambda n And
(5) And stopping iteration when the Lagrangian multiplier update change of the two iterations is smaller than a set threshold.
Further, the second objective function is expressed as:
wherein W is 0 And W is n The net benefit of the hybrid energy storage system and the microgrid N, respectively, N representing the number of microgrids.
Further, the net gains of the hybrid energy storage system and the micro grid n are respectively:
wherein, representing the cost of the hybrid energy storage system when there is no transaction between the micro grid and the hybrid energy storage system, C 0 Is the cost of the hybrid energy storage system solved in S23,/-, for>And->Representing the amount of energy purchased by the micro-grid n from the hybrid energy storage system and the amount of energy sold to the hybrid energy storage system, respectively,/->Representing the cost when the micro grid n cannot trade with the hybrid energy storage system, C n Is the cost of the micro grid n solved in S23,/-, for>Andrepresenting the amount of the purchased energy and the amount of the sold energy of the micro-grid respectively, and solving the objective function to obtain the amount tau of the purchased energy of the micro-grid buy And the amount tau of the energy sold by the micro-grid sell Thus completing the settlement of the whole business process.
The second aspect of the present invention provides a renewable energy-oriented multi-energy microgrid shared energy storage control system, comprising: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium, and execute the renewable energy-oriented multi-energy micro-grid sharing energy storage control method according to the first aspect of the present invention.
Compared with the prior art, the optimal control scheme for energy storage and energy sharing of all multi-energy micro-grids is realized through distributed decision, the electric power and natural gas purchase cost of the multi-energy micro-grids and the energy storage operation cost of an energy storage party are fully considered, the optimal control problem is solved through a distributed method to make decisions, and the renewable energy utilization rate of the micro-grids can be obviously improved under the condition of lower investment cost of an energy storage system due to the distributed optimization algorithm and the thermoelectric hybrid energy storage mode. And after the optimization control problem is solved, transaction amount of the micro-grid and the hybrid energy storage system is obtained through a Nash equilibrium strategy, so that a complete business control method is realized. The distributed control characteristic of the invention avoids the privacy protection problem related to centralized optimization control, and the calculation power of each micro-grid node is utilized to fully reduce the calculation burden of a calculation center. The energy storage and energy sharing control method mainly realizes the local consumption of renewable energy sources, reduces energy abandonment and reduces dependence of the micro-grid on external energy sources such as a power grid, natural gas and the like.
Drawings
FIG. 1 is a flow chart of a renewable energy oriented multi-energy micro-grid shared energy storage control method provided by the invention;
FIG. 2 is a schematic diagram of a multi-microgrid energy system framework provided by the present invention;
fig. 3 is a schematic diagram of the internal energy flow of the hybrid energy storage system provided by the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not interfere with each other.
The invention provides a renewable energy source-oriented multi-energy source micro-grid sharing energy storage control method, which comprises the following steps:
s1, taking the total cost of a micro-grid cluster and a hybrid energy storage system as a first objective function, taking the electric quantity and the natural gas quantity purchased from the outside of the micro-grid, the energy flow inside a single micro-grid, the energy storage loss cost of the hybrid energy storage system, the charge and discharge speed of the hybrid energy storage system, the thermoelectric conversion of the hybrid energy storage system, the direct energy flow of the micro-grid and the hybrid energy storage system as first decision variables, and constructing constraint conditions for each first decision variable so as to construct a multi-energy micro-grid shared energy storage control model comprising the first decision variables, the first objective function and the constraint conditions;
s2, solving a constructed multi-energy micro-grid shared energy storage control model by adopting a distributed optimization method;
s3, adopting a Nash equilibrium strategy, after obtaining the optimal solution in the step S2, maximizing the product of the net benefits of all the micro-grids and the hybrid energy storage system to be a second objective function, and calculating the transaction amount of each micro-grid and the hybrid energy storage system by taking the transaction amount of each micro-grid and the hybrid energy storage system as a second decision variable to obtain a control scheme of sharing multiple energy storage by multiple micro-grids.
Specifically, the first objective function is expressed as:
s.t.x n ∈X n ，y∈Y
wherein x is n Representing the decision variable of the micro-grid n, X n Representing the decision variable x n Y represents a hybrid energy storage system decision variable, Y represents a hybrid energy storage system decision variable constraint set, C n (x n ) Representing the cost of the micro grid n, C 0 (y) represents the running cost of the hybrid energy storage system and N represents the number of micro-grids.
Specifically, the cost of the micro grid n is expressed as:
wherein, representing the cost of the micro grid n purchasing power from the main grid at time t,representing the cost of the micro grid n to purchase natural gas at time t,/->And g n，t Representing the electric power and the natural gas volume purchased by the micro grid n from the main grid at time t, respectively,/->And gamma gas Representing the price of the electricity purchase and the price of the natural gas purchase, respectively.
Specifically, the operating cost of the hybrid energy storage system is expressed as:
wherein, and->Operating costs of the energy storage battery and the heat storage device, respectively, < >>And->Respectively representing the charge power and the discharge power of the energy storage battery，/>And->The charging power and the discharging power of the heat storage device are respectively represented.
Specifically, decision variable x n Is represented as follows:
decision variable x n Is a constraint set X of (1) n The expression is as follows:
wherein, and->Representing the electric power and the natural gas volume purchased by the micro grid n from the main grid at time t, respectively,/->And->Representing natural gas for micro-grid gas turbines and gas boilers, respectively, < >>For the heat production of a gas turbine, +.>For the heat production efficiency of the gas turbine, L is the heating value of the natural gas, < >>For the amount of electricity produced by the gas turbine,for the power generation efficiency of a gas turbine, +.>And->Respectively represents the heat generation amount and the electricity generation efficiency of the gas boiler,and->Respectively representing the refrigerating capacity, refrigerating efficiency and consumed heat of the absorption refrigerator, +.>Andrespectively representing the refrigerating capacity, refrigerating efficiency and consumed electric quantity of the electric refrigerator, +.>Renewable energy generation capacity of a surface micro-grid, < -> And->Respectively representing the electric, thermal and cold loads of the micro-grid, < ->And->Respectively represents the wasted electric energy and heat energy of the micro-grid due to incapacitation, and the micro-grid is in a +.>And->The method comprises the steps of respectively representing electric energy and heat energy of a micro-grid and a hybrid energy storage system in a transaction mode, and representing that the micro-grid purchases energy from the hybrid energy storage system when the value is positive, and representing that the micro-grid sells the energy to the hybrid energy storage system when the value is negative;
the decision variable y is expressed as follows:
the constraint set Y of the decision variable Y is expressed as follows:
wherein S is t Indicating the energy level of the energy storage battery at time t,and->Respectively representing the charge and discharge efficiency of the energy storage battery, +.>And->Respectively represent the charge and discharge power of the energy storage battery, S min And S is max Respectively representing the lower limit and the upper limit of the energy level of the energy storage battery, < >>And->Respectively represent the maximum power of charging and discharging of the energy storage battery, H t Indicating the energy level of the heat storage system at time t, < >>And->Respectively representing the heat charging and discharging efficiency of the heat storage system, +.>And->Respectively representing the charging and discharging power of the energy storage battery, and Hmin and Hmax respectively representing the lower limit and the upper limit of the energy level of the heat storage system, < + >>Andmaximum power of heat storage system for heat charging and heat discharging, respectively,/->η eh And->Indicating the heat generation amount, heat generation efficiency and power consumption of the electric boiler,/->And->Representing the sum of electric energy or heat energy respectively traded by the hybrid energy storage system and the micro-grid, and if the sum is negative, representing that the hybrid energy storage system integrally purchases energy from the micro-grid, regularly representing that the hybrid energy storage system integrally sells energy to the micro-grid.
Specifically, step S2 includes the steps of:
s21, introducing auxiliary variablesAnd->Will restrict the set X n Coupling constraints in (a)
Decoupling is a pairwise coupling constraint->And independent constraint->Introducing the auxiliary variable +.>Andcoupling constraint in constraint set Y +.>Decoupling into pairwise coupling constraintsAnd independent constraint->
The multi-energy micro-grid shared energy storage control model is converted into:
wherein lambda is n，t Andrepresenting the pair multiplier of the corresponding constraint;
s22, constructing the following Lagrangian function based on the converted objective function:
s.t.x n ∈X n ，y∈Y，θ∈Z
wherein μ and ν represent given penalty parameters, q n And r is an auxiliary variable which is used as a reference,andthe method respectively represents the amount of energy purchased by the micro-grid from the hybrid energy storage system and the amount of energy sold by the hybrid energy storage system to the micro-grid, and Z is +.>And->
S23, solving the Lagrangian function for all decision variables through collaborative distributed iteration of an alternate direction multiplier method, so that an optimal solution is obtained.
Specifically, in step S22, when the lagrangian function is solved by using the alternate direction multiplier method, the current iteration number is represented by k, and in each iteration, the following steps are required to be executed:
(1) Updating decision variables of microgrid n
Wherein the method comprises the steps ofIs x n Is a sub-vector of (2);
(2) Updating decision variables of a hybrid energy storage system
Wherein e sh Is a sub-vector of y;
(3) Updating auxiliary variables
(4) Updating lagrangian multiplier lambda n And
(5) And stopping iteration when the Lagrangian multiplier update change of the two iterations is smaller than a set threshold.
Specifically, the second objective function is expressed as:
wherein W is 0 And W is n The net benefit of the hybrid energy storage system and the microgrid N, respectively, N representing the number of microgrids.
Specifically, the net gains of the hybrid energy storage system and the micro grid n are respectively:
wherein, representing the cost of the hybrid energy storage system when there is no transaction between the micro grid and the hybrid energy storage system, C 0 Is the cost of the hybrid energy storage system solved in S23,/-, for>And->Representing the amount of energy purchased by the micro-grid n from the hybrid energy storage system and the amount of energy sold to the hybrid energy storage system, respectively,/->Representing the cost when the micro grid n cannot trade with the hybrid energy storage system, C n Is the cost of the micro grid n solved in S23,/-, for>Andrepresenting the amount of the purchased energy and the amount of the sold energy of the micro-grid respectively, and obtaining the gold of the purchased energy of the micro-grid by solving the objective functionFrontal tau buy And the amount tau of the energy sold by the micro-grid sell Thus completing the settlement of the whole business process.
Examples
The multi-energy micro-grid is provided with renewable energy power generation equipment, a combined cooling, heating and power system (CCHP) and an electric refrigerator so as to realize the load demands of cooling, heating and electricity. The common energy storage device is a hybrid energy storage system having an energy storage battery, a heat storage device and an electric boiler, with which the micro-grid can purchase or sell electric or thermal energy. Inside the hybrid energy storage system, electrical energy that cannot be consumed by the energy storage battery can be converted into thermal energy by an electric boiler and stored in the heat storage device. The hybrid energy storage system is provided with a controller and a computing center, and can realize optimal energy storage and energy sharing control of a plurality of micro-grids.
The present embodiment makes a distributed decision on the amount of energy exchanged between all micro-grids and the hybrid energy storage system. The goal of the decision is to minimize the electricity purchase costs of all micro-grids, the gas purchase costs, and the operation of the energy storage cells and heat storage devices in the hybrid energy storage system. The distributed control characteristics avoid privacy protection problems related to centralized optimization control, and the calculation power of each micro-grid node is utilized, so that the calculation load of a hybrid calculation center can be fully reduced; the thermoelectric energy storage and energy sharing control method mainly realizes the local consumption of renewable energy sources, reduces energy abandonment and reduces dependence of the micro-grid on external energy sources such as a power grid, natural gas and the like.
As in fig. 1, therefore, the energy system optimization control problem is established first. As shown in fig. 2, it is assumed that n=1, 2,...Representing electricity purchased by a micro grid from a main grid g n，t Representing natural gas purchased by the microgrid. Cost of micro grid nTowel->And->Representing the cost of purchasing power or natural gas at time t for the micro grid n, respectively +.>And gamma gas Representing the price of the electricity purchase and the price of the natural gas purchase, respectively. The CCHP system of the micro-grid consists of a gas turbine, a gas boiler and an absorption refrigerator. Natural gas g purchased by micro-grid n，t Can be used for gas turbine->And gas boiler->The gas turbine can simultaneously generate heat and electricity, and the generated heat and the generated electricity are respectively: />Wherein L is the calorific value of natural gas, +.>Andthe heat and electricity generating efficiency of the gas turbine, respectively. The gas-fired boiler can only produce heat, and the heat production amount is +.>Wherein->Is the heat generating efficiency of the gas boiler. The refrigerating capacity of the absorption refrigerator is +.>Wherein->Is the energy efficiency ratio of the absorption refrigerator. The micro-grid can also be supplied with cold by an electric refrigerator, the refrigerating capacity of which is +.>Wherein->Is the energy efficiency ratio of the electric refrigerator. Each microgrid needs to meet the following energy balance:
the above formula represents the energy balance of the three loads of electricity, heat and cold of the micro-grid. Wherein, the generating capacity of renewable energy sources of the micro-grid mainly comprises wind power generation and solar photovoltaic power generation. /> Respectively representing the requirements of three loads of electricity, heat and cold. />And->Respectively, the electric energy and the heat energy wasted due to the non-digestion. />And->And respectively representing electric energy and heat energy which are traded by the micro-grid and the hybrid energy storage system, wherein when the value is positive, the micro-grid purchases energy from the hybrid energy storage system, and when the value is negative, the micro-grid sells the energy to the hybrid energy storage system.
The hybrid energy storage system consists of an energy storage battery, a heat storage device and an electric boiler. The cost of the hybrid energy storage system is mainly the running cost thereofWherein->And->The running costs of the energy storage battery and the heat storage device are mainly related to the charge and discharge power and the charge and discharge power. The energy storage battery needs to meet the following charge-discharge constraints:
/>
S min ≤S t ≤S max
the first line of the equation represents the energy level S of the energy storage cell at time t t The second row represents the constraints of charge and discharge power and the third row represents the constraints of energy level. Likewise, the heat storage device also satisfies the following constraints:
H min ≤H t ≤H max
likewise, the energy level H of the first-row-table heat storage device of the formula at time t t The second row represents the constraints of charge and discharge power and the third row represents the constraints of energy level.
The use of an electric boiler enables complex electrothermal energy flows by the energy storage battery, the specific form of which is illustrated in fig. 3 of the drawings. Heat generation of electric boilerη eh For its transformation efficiency, ++>Electrical energy consumed for its heat generation. The energy flow balance present in the energy storage system can be obtained in connection with fig. 3:
and->The trade amounts of electric energy and heat energy of the hybrid energy storage system and the micro-grid are respectively represented. And when the value is positive, the hybrid energy storage system is used for selling energy to the micro-grid. When its value is negative, it indicates that the hybrid system is purchasing energy from the micro grid.
The objective of the proposed optimization control problem of the present invention is to solve the optimal value of the sum of all microgrids and hybrid energy storage system costs:
s.t.x n ∈X n ，y∈Y
X n representing constraints involved in solving the optimal control problem for the micro grid n, and Y represents constraints involved in solving the optimal control problem for the hybrid energy storage system. The invention adopts an alternate multiplier algorithm to solve the optimization control problem. Defining vectorsAnd->Then introducing an auxiliary variable q n And r, which correspond to the micro grid n and the hybrid energy storage system respectively, the auxiliary variables need to satisfy constraints:
thus, the following Lagrangian function can be constructed:
mu > 0 and upsilon > 0 are penalty parameters, which are fixed values. Lambda (lambda) n Andthe Lagrangian multiplier corresponds to the micro grid n and the hybrid energy storage system respectively. The alternative multiplier algorithm can decompose the formula, so that each micro-grid and the hybrid energy storage system can obtain an optimal solution by solving the own sub-problem.
The sub-problem of the micro-grid is shown below, and the variable x of the next iteration can be obtained by solving the problem n (k+1)。
/>
The variables: x is x n
It is known that: q n (k)，λ n (k)
s.t.X n
The sub-problem of the hybrid energy storage system is shown below, and the variable y (k+1) for the next iteration can be obtained by solving the problem.
The variables: y is
It is known that: r (k),
s.t.Y
after the optimization result is obtained, the computing center of the hybrid energy storage system can also solve the following problem to update the auxiliary variable to obtain q n (k+1) and r (k+1).
The variables: e, e 1 ，e 2 ，...，e N ，q
It is known that:e sh (k+1)
s.t.(6)
the lagrangian multiplier is then updated as follows:
the complete alternate multiplier-algorithm flow is shown in Table 1:
TABLE 1
The optimal control problem designed in the invention can be completely solved by the collaborative distribution of all micro-grids and the hybrid energy storage system through an alternate direction multiplier method. After completion of the solution, all micro-organismsThe thermoelectric transaction amounts of the grid and the hybrid energy storage system are determined. The transaction amount between each micro grid and the hybrid energy storage system is then determined by a nash equalization strategy. When solving Nash equilibrium, defining the cost of the micro-grid n and the hybrid energy storage system when no energy is stored asAndnet gain of the micro grid n can then be achieved +.>And net benefit of hybrid energy storage systemsWherein->And->Representing the amount of money traded by the micro-grid n for buying or selling energy from the hybrid energy storage system, respectively, by solving +.>Can get +.>And->Is a solution to the optimization of (3).
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (7)

1. The renewable energy source oriented multi-energy source micro-grid sharing energy storage control method is characterized by comprising the following steps of:
s1, taking the total cost of a micro-grid cluster and a hybrid energy storage system as a first objective function, taking the electric quantity and the natural gas quantity purchased from the outside of the micro-grid, the energy flow inside a single micro-grid, the energy storage loss cost of the hybrid energy storage system, the charge and discharge speed of the hybrid energy storage system, the thermoelectric conversion of the hybrid energy storage system, the direct energy flow of the micro-grid and the hybrid energy storage system as first decision variables, and constructing constraint conditions for each first decision variable so as to construct a multi-energy micro-grid shared energy storage control model comprising the first decision variables, the first objective function and the constraint conditions; the first objective function is expressed as:
s.t.x n ∈X n ,y∈Y
wherein x is n Representing the decision variable of the micro-grid n, X n Representing the decision variable x n Y represents a hybrid energy storage system decision variable, Y represents a hybrid energy storage system decision variable constraint set, C n (x n ) Representing the cost of the micro grid n, C 0 (y) represents an operation cost of the hybrid energy storage system, and N represents the number of micro-grids;
s2, solving a constructed multi-energy micro-grid shared energy storage control model by adopting a distributed optimization method; the method comprises the following steps:
s21, introducing auxiliary variablesAnd->Will restrict the set X n Coupling constraints in (a)
Decoupling is a pairwise coupling constraint->And independent constraint->Wherein (1)>Representing renewable energy generation of a microgrid, < +.>Representing the electrical energy power purchased by the micro grid n from the main grid at time t, < >>For the power production of a gas turbine, +.>For the heat production of a gas turbine, +.>Indicating the heat production of the gas boiler, +.>Indicating the heat consumed by the absorption chiller, +.>Representing the amount of electricity consumed by an electric refrigerator, +.>And->Representing the electric and thermal loads of the micro-grid respectively,/->And->Respectively represents the wasted electric energy and heat energy of the micro-grid due to incapacitation, and the micro-grid is in a +.>And->The method comprises the steps of respectively representing electric energy and heat energy of a micro-grid and a hybrid energy storage system in a transaction mode, and representing that the micro-grid purchases energy from the hybrid energy storage system when the value is positive, and representing that the micro-grid sells the energy to the hybrid energy storage system when the value is negative;
introducing auxiliary variablesAnd->Coupling constraint in constraint set Y +.>Decoupling is a pairwise coupling constraint->And independent constraint->Wherein (1)>And->Respectively representing the charge power and the discharge power of the energy storage battery, < >>And->Respectively representing the charging power and the discharging power of the heat storage device, < >>And->Indicating the heat and electricity production of the electric boiler, +.>And->Respectively representing the sum of electric energy and heat energy of the transaction of the hybrid energy storage system and the micro-grid, and if the sum is negative, representing that the hybrid energy storage system integrally purchases energy from the micro-grid, and regularly representing that the hybrid energy storage system integrally sells energy to the micro-grid;
the multi-energy micro-grid shared energy storage control model is converted into:
wherein lambda is n，t Andrepresenting the pair multiplier of the corresponding constraint;
s22, constructing the following Lagrangian function based on the converted objective function:
s.t.x n ∈X n y∈Y，θ∈Z
wherein μ and ν represent given penalty parameters, q n And r is an auxiliary variable which is used as a reference,and->Representing the amount of energy purchased by the micro-grid from the hybrid energy storage system and the amount of energy sold by the hybrid energy storage system to the micro-grid respectively, wherein Z isAnd->When solving the Lagrangian function by adopting the alternate direction multiplier method, the current iteration number is represented by k, and the following steps are required to be executed in each iteration:
(1) Updating decision variables of microgrid n
Wherein the method comprises the steps ofIs x n Is a sub-vector of (2);
(2) Updating decision variables of a hybrid energy storage system
Wherein e sh Is a sub-vector of y;
(3) Updating auxiliary variables
(4) Updating lagrangian multiplier lambda n And
(5) Stopping iteration when the updating change of the Lagrangian multiplier of the two iterations is smaller than a set threshold value;
s23, solving the Lagrangian function for all decision variables through collaborative distributed iteration of an alternate direction multiplier method, so as to obtain an optimal solution;
s3, adopting a Nash equilibrium strategy, after obtaining the optimal solution in the step S2, maximizing the product of the net benefits of all the micro-grids and the hybrid energy storage system to be a second objective function, and calculating the transaction amount of each micro-grid and the hybrid energy storage system by taking the transaction amount of each micro-grid and the hybrid energy storage system as a second decision variable to obtain a control scheme of sharing multiple energy storage by multiple micro-grids.
2. The method of claim 1, wherein the cost of the microgrid n is expressed as:
wherein, representing the cost of the micro grid n purchasing power from the main grid at time t,representing the cost of the micro grid n to purchase natural gas at time t,/->And g n，t Representing the electric power and the natural gas volume purchased by the micro grid n from the main grid at time t, respectively,/->And gamma gas Representing the price of the electricity purchase and the price of the natural gas purchase, respectively.
3. The method of claim 1, wherein the operating cost of the hybrid energy storage system is expressed as:
wherein, and->Operating costs of the energy storage battery and the heat storage device, respectively, < >>And->Respectively represent the charging power sum of the energy storage batteriesDischarge power, < >>And->The charging power and the discharging power of the heat storage device are respectively represented.
4. The method of claim 1, wherein the decision variable x n Is represented as follows:
decision variable x n Is a constraint set X of (1) n The expression is as follows:
wherein, and g n，t Representing the electrical power and the natural gas volume purchased by the micro grid n from the main grid at time t,and->Represents the volume of natural gas used by the micro-grid gas turbine and the gas boiler respectively, < >>For the heat production of a gas turbine, +.>For the heat production efficiency of the gas turbine, L is the heating value of the natural gas, < >>For the power production of a gas turbine, +.>For the power generation efficiency of a gas turbine, +.>And->Respectively representing the heat production amount and the electricity production efficiency of the gas boiler, < ->Andrespectively representing the refrigerating capacity, refrigerating efficiency and consumed heat of the absorption refrigerator, +.>And->Respectively representing the refrigerating capacity, refrigerating efficiency and consumed electric quantity of the electric refrigerator, +.>Represents the renewable energy generation capacity of the micro-grid,and->Respectively representing the electric, thermal and cold loads of the micro-grid, < ->And->Respectively represents the wasted electric energy and heat energy of the micro-grid due to incapacitation, and the micro-grid is in a +.>And->The method comprises the steps of respectively representing electric energy and heat energy of a micro-grid and a hybrid energy storage system in a transaction mode, and representing that the micro-grid purchases energy from the hybrid energy storage system when the value is positive, and representing that the micro-grid sells the energy to the hybrid energy storage system when the value is negative;
the decision variable y is expressed as follows:
the constraint set Y of the decision variable Y is expressed as follows:
wherein S is t Indicating the energy level of the energy storage battery at time t,and->Respectively representing the charge and discharge efficiency of the energy storage battery, +.>And->Respectively represent the charge and discharge power of the energy storage battery, S min And S is max Respectively representing the lower limit and the upper limit of the energy level of the energy storage battery, < >>And->Respectively represent the maximum power of charging and discharging of the energy storage battery, H t Indicating the energy level of the heat storage system at time t, < >>And->Respectively representing the heat charging and discharging efficiency of the heat storage system, +.>And->Respectively represent the charge and discharge power, H of the heat storage system min And H max Representing the lower and upper limit, respectively, of the energy level of the heat storage system,/->And->Maximum power of heat storage system for heat charging and heat discharging, respectively,/->η eh And->Indicating the heat generation amount, heat generation efficiency and power consumption of the electric boiler,/->And->Representing the sum of electric energy and the sum of heat energy respectively which are traded by the hybrid energy storage system and the micro-grid, and if the sum of the electric energy and the sum of the heat energy is negative, representing that the hybrid energy storage system integrally purchases energy from the micro-grid, and regularly representing that the hybrid energy storage system integrally sells energy to the micro-grid.
5. The method of claim 1, wherein the second objective function is represented as:
wherein W is 0 And W is n The net benefit of the hybrid energy storage system and the microgrid N, respectively, N representing the number of microgrids.
6. The method of claim 5, wherein the net gains of the hybrid energy storage system and the microgrid n are respectively:
wherein, representing the cost of the hybrid energy storage system when there is no transaction between the micro grid and the hybrid energy storage system, C 0 Is the cost of the hybrid energy storage system solved in step S23, +.>And->Representing the amount of energy purchased by the micro-grid n from the hybrid energy storage system and the amount of energy sold to the hybrid energy storage system, respectively,/->Representing the cost when the micro grid n cannot trade with the hybrid energy storage system, C n Is the cost of the micro grid n solved in step S23,/->Andrepresenting the amount of energy purchased by the micro-grid and the amount of energy sold respectively.
7. Renewable energy-oriented multi-energy micro-grid shared energy storage control system is characterized by comprising: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and execute the renewable energy oriented multi-energy microgrid sharing energy storage control method according to any one of claims 1 to 6.
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