CN110601183B - Ocean island micro-grid system and distributed periodic energy trading method thereof - Google Patents
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Abstract
The invention discloses an ocean island micro-grid system and a distributed periodic energy trading method thereof, and belongs to the field of ocean island micro-grid energy management. The system comprises: the energy center stores energy periodically transported from the continent to the island and electric energy generated by power generation of renewable energy on the island, and provides electric energy for load of the island microgrid; the aggregator is used for determining the electric energy obtained from the energy center and the electric energy transaction price of the end user according to the electric energy transaction demand of the end user, and scheduling the charging and discharging amount of the energy storage system; the energy storage system acquires electric energy from the energy center according to the scheduling of the aggregator and provides the electric energy for the terminal user; and the end user determines the electric energy transaction amount with the energy storage system according to the electric energy transaction price of the aggregator. The method can maximize the benefits of the aggregator, minimize the power consumption cost of each user, preferentially meet the power consumption requirements of strategic users, and ensure the reliable and economic operation of the island micro-grid system.
Description
Technical Field
The invention belongs to the field of ocean island microgrid energy management, and particularly relates to an ocean island microgrid system and a distributed periodic energy trading method thereof.
Background
The earth has a plurality of ocean islands which are not only national defense sentinels but also symbols of national leadership and are an important guarantee for the integrity of national territories and leadership. Providing stable power supply for ocean islands is crucial to work and life on the island. Since the ocean island is far from the continent, it is difficult to directly connect the ocean island to the main grid on the continent. Thus, the energy demand on ocean islands is partly met by the supply of distributed renewable energy generators on or near the islands and partly by ships transporting some stored energy and also other materials from the continents for long periods (usually one week or even longer). Because renewable energy has the characteristics of randomness, volatility and intermittency, and the energy resources of the two parts are limited, it is unlikely that the main grid will provide reliable energy resources for residential users on ocean islands. Therefore, maintaining balance of supply and demand on ocean islands presents new challenges.
To date, the problems of microgrid energy management are mainly divided into two categories: one is to assume that the microgrid is connected to and is provided with sufficient energy by the main grid, however this situation may not be suitable for an ocean island microgrid scenario, where the load in the island microgrid is physically disconnected from the main grid due to being remote from the continent; and secondly, although the island micro-grid is not connected with the main grid, the island micro-grid is assumed to have sufficient energy supply, namely the energy demand in the island micro-grid can be fully met. Different from the two situations, the renewable energy source periodic power generation on the ocean island has high uncertainty, the energy supply in the ocean island micro-grid can not guarantee to meet the energy requirements of all loads, and compared with the common load, the energy requirements of strategic loads in the ocean island micro-grid need to be preferentially met, so that the reliable operation of the ocean island micro-grid is guaranteed to have great challenge. In addition, the traditional optimization scheduling adopts a centralized method, the privacy information (such as the power consumption and the power generation amount information) of the user cannot be protected, and the calculation efficiency is low.
In general, there is a need to develop effective energy management strategies to ensure reliable operation of ocean island micro-grids.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide an ocean island microgrid system and a distributed periodic energy trading method thereof, and aims to solve the problems that the existing ocean island microgrid energy management method is low in operation reliability and cannot provide stable electric energy for users.
One aspect of the present invention provides an ocean island microgrid system, comprising: the system comprises an energy center, an aggregator, an energy storage system and an end user;
the energy center is used for storing energy periodically transported from the continent to the ocean island and electric energy generated by power generation of renewable energy on the ocean island and providing electric energy for the load of the island microgrid;
the aggregator is used for determining the electric energy acquired from an energy center and the electric energy transaction price of the end user according to the electric energy transaction demand of the end user, and scheduling the charging and discharging amount of the energy storage system;
the energy storage system is used for acquiring electric energy from the energy center according to the scheduling of the aggregator and providing the acquired electric energy for the terminal user;
and the terminal user is used for determining the electric energy transaction amount with the energy storage system according to the electric energy transaction price of the aggregator.
Further, the end user configures an independent photovoltaic power generation system to provide electric energy for the end user.
Further, the end users comprise strategic users and ordinary users; the electric energy demand of the strategic user is used for public infrastructure, and the electric energy supply priority of the strategic user is higher than that of the ordinary user; the electric energy requirement of the ordinary user is used for daily life.
The invention further provides a distributed periodic energy trading method for the ocean island micro-grid system, which comprises the following steps:
(1) the aggregator preliminarily obtains the electricity purchasing quantity and the electric energy transaction price which enable the aggregator to be most beneficial according to the electric energy supply constraint of the energy center, the uncertain constraint of renewable energy power generation, the charge-discharge constraint of the energy storage system and the electric energy transaction price constraint;
(2) the terminal user preliminarily determines the electric energy transaction amount which enables the electricity consumption cost of each terminal user to be minimum according to the electric energy transaction price preliminarily determined by the aggregator, the energy balance constraint of the terminal user, the uncertain photovoltaic power generation constraint and the load energy consumption upper and lower limit constraints of the terminal user;
(3) the aggregator updates the electricity purchasing quantity and the electricity trading price according to the electricity trading quantity fed back by the terminal user, and finally obtains the optimal electricity purchasing quantity and the optimal electricity trading price which enable the aggregator to have the maximum benefit;
(4) the terminal user updates the electric energy transaction amount according to the optimal electric energy transaction price, and finally the optimal electric energy transaction amount which enables the electricity consumption cost of each terminal user to be minimum is obtained;
(5) and the aggregator acquires electric energy from an energy center according to the optimal electricity purchasing quantity, and the terminal user carries out electric energy transaction with an energy storage system according to the optimal electric energy transaction quantity.
Further, the power supply constraint of the energy center is as follows:
wherein e (t) represents the amount of electric energy purchased by the aggregator from the energy center for time period t, L (t)maxRepresenting the maximum load that the energy center can supply during the time period t, EtRepresenting energy transported to the ocean island, ErRepresenting the total amount of renewable energy power generation on the ocean island in one scheduling period, and representing the time period of one scheduling period as
H represents the time period number of a scheduling period, wherein the scheduling period refers to the transportation period of energy from continents to the ocean island;
further, the renewable energy power generation uncertainty constraint is expressed as:
wherein,
representing the nominal total amount of renewable energy generation during a scheduling period,rthe robust parameters are represented by a robust parameter,rrepresents the maximum error value of the power generation of the renewable energy source,
further, the charge and discharge constraints of the energy storage system are as follows:
wherein alpha is more than 0 and less than or equal to 1 to represent the leakage rate of the energy storage system, q (t-1) represents the charge level of the energy storage system at the beginning of the time period t, and eta+And η-Respectively show the charging and discharging efficiency of the energy storage system,
and
respectively representing the total charge and the total discharge of the energy storage system in a time period t, and all end users
It is shown that,
and
representing the power supplied to and drawn from the energy storage system by end user n during time period t, Q, respectivelymRepresenting the maximum capacity of the energy storage system.
Further, the electric energy transaction price constraint is:
where a (t) represents the electric energy trade price established by the aggregator, λ (t) represents the electric energy price of the energy center, and λ (t) ═ Φte(t)+t，φtAndtis a constant number of times, and is,
cn(t)maxrepresenting a maximum end user load less than the line power,
cn(t)minrepresenting the end user minimum load.
Further, the benefit R of the aggregator in one scheduling period is:
wherein x isnAnd (t) represents the electric energy transaction amount of the end user n and the energy storage system.
Further, the energy balance constraint of the end user is:
xn(t)＝gn(t)-cn(t)
wherein, gn(t) represents the supply of the photovoltaic power generation system to the end user n, cn(t) is the actual power consumption of the end user;
the photovoltaic power generation uncertainty constraint is expressed as:
wherein,
representing the nominal supply of the photovoltaic power generation system to the end user n,nthe robust parameters are represented by a robust parameter,n(t) represents a maximum error value of the photovoltaic power generation system.
The upper and lower limits of the load energy consumption of the terminal user are constrained as follows:
cn(t)min≤cn(t)≤cn(t)max
the electric energy use cost C of the terminal usern(t) is:
Cn(t)＝-a(t)xn(t)+Sn(cn(t),dn(t))
wherein S isn(cn(t),dn(t))＝αndn(t)ln[(dn(t)+βn)/(cn(t)+βn)]Function representing the end user satisfaction of electric energy usage, dn(t) is the nominal power demand, α, of the end usernIndicating the priority of power supply, alpha, to the user nn,βn＞0。
Through the technical scheme, compared with the prior art, the invention has the following beneficial effects:
(1) the invention provides a novel ocean island microgrid system which comprehensively considers factors such as the limitation of energy resources transported to an ocean island, the priority of energy supply of different terminal users, the uncertainty of the height of renewable energy power generation and the like, can effectively solve the problem of energy supply of the ocean island microgrid, preferentially meets the power utilization requirements of strategic users, and ensures the reliable and economic operation of the ocean island microgrid system.
(2) The method adopts a robust optimization method to process the uncertainty problem of renewable energy power generation, realizes the bidirectional interaction process between the aggregator and the terminal users through a dynamic non-cooperative Stackelberg game framework, and designs a distributed two-layer iterative algorithm to find a Stackelberg balance strategy, namely, the optimal electricity purchasing quantity, the optimal electricity trading price and the optimal electricity trading quantity of each terminal user of the aggregator are obtained, so that the benefits of the aggregator are maximized and the electricity cost of each user is minimized.
(3) Compared with the traditional optimization scheduling method which adopts a centralized method, the distributed two-layer iterative algorithm designed by the invention can make independent decisions for each part of the microgrid system, not only can protect the privacy information of users and improve the calculation efficiency, but also can be applied to solving the energy management problem of the large-scale ocean island microgrid.
Drawings
Fig. 1 is a structural diagram of an ocean island microgrid system provided by the invention;
fig. 2 is a flow chart of a distributed periodic energy trading method of an ocean island micro-grid system based on the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, one aspect of the present invention provides an ocean island microgrid system, comprising: the system comprises an energy center, an aggregator, an energy storage system and an end user; the energy center is used for storing energy periodically transported to an ocean island from a continent by a ship and energy generated by power generation of renewable energy sources (such as photovoltaic energy, wind energy, wave energy and ocean current energy) on the ocean island and providing electric energy for a load of an island microgrid; the aggregator is used for determining the electric energy obtained from the energy center and the electric energy transaction price of the end user according to the electric energy transaction demand of the end user, and scheduling the charging and discharging amount of the energy storage system; the energy storage system is used for acquiring electric energy from an energy center according to the scheduling of the aggregator and providing the acquired electric energy for the terminal user; and the end user is used for determining the electric energy transaction amount with the energy storage system according to the electric energy transaction price of the aggregator. Each end user is provided with an independent photovoltaic power generation system to provide electric energy for the end users. The terminal users comprise strategic users and ordinary users; strategic users' electrical energy needs for public infrastructure such as transportation, medical and defense, with energy supply priorities higher than that of ordinary users; energy needs of ordinary users are used in daily life, such as refrigerators, lamps, and washing machines.
As shown in fig. 2, another aspect of the present invention provides a distributed periodic energy trading method based on the ocean island microgrid system, and the main ideas are as follows: firstly, respectively and properly modeling an optimization problem of an end user and an optimization problem of an aggregator, wherein the optimization aims to simultaneously minimize the electricity consumption cost of each user and maximize the benefit of the aggregator; and then implementing a dynamic non-cooperative Stackelberg game framework to realize a bidirectional interaction process between the aggregator and the terminal user, designing a distributed two-layer iterative algorithm to find a Stackelberg balancing strategy to enable the benefits of the aggregator to be maximum and the power consumption cost of each user to be minimum, and implementing the dynamic non-cooperative Stackelberg game framework can not only protect the privacy information of the users, but also reduce the calculation burden. The aggregator is used as a leader, firstly, the energy purchasing quantity from the energy center and the electric energy trading price of the end user, which enable the benefits of the aggregator to be maximum, are determined, the electric energy trading price information is informed to all users, then, each user determines the optimal electric energy trading quantity with the energy storage system, which enables the electricity utilization cost of the user to be minimum, according to the electric energy trading price information set by the aggregator, and the optimal electric energy trading quantity is informed to the aggregator. The method specifically comprises the following steps:
(1) the aggregator preliminarily obtains the electricity purchasing quantity and the electric energy transaction price which enable the aggregator to be most beneficial according to the electric energy supply constraint of the energy center, the uncertain constraint of renewable energy power generation, the charge-discharge constraint of the energy storage system and the electric energy transaction price constraint;
specifically, the benefits of the aggregator include the trading revenue with each end user and the cost of electricity from the energy center, and the benefit R of the aggregator over a scheduling period can be expressed as:
the method takes the transportation period of energy transported from continents to ocean islands as a scheduling period, and one scheduling period time period is expressed as
H represents the number of time periods of a scheduling cycle, a (t) represents the electric energy transaction price established by the aggregator, xn(t) represents the electric energy transaction amount of the end user n and the energy storage system, lambda (t) represents the energy price of the energy center, and lambda (t) is phite(t)+tAnd e (t) represents the amount of electrical energy, phi, purchased by the aggregator from the energy center for time period ttAndtis a constant. The constraints which need to be met by optimizing the benefits of the aggregator include the constraint of power supply of an energy center, the uncertain constraint of power generation of renewable energy sources, and the constraint of charging and discharging of an energy storage systemBundle and electric energy trade price constraints, wherein the electric energy supply constraints of the energy center are:
wherein, L (t)maxRepresenting the maximum load that the energy center can supply during the time period t, EtRepresenting energy transported to the ocean island, ErRepresenting the total amount of power generation of renewable energy sources on the ocean island in a scheduling period;
the uncertain constraint of renewable energy power generation is expressed as:
wherein,
representing the nominal total amount of renewable energy generation during a scheduling period,rthe robust parameters are represented by a robust parameter,rrepresents the maximum error value of the power generation of the renewable energy source,
the charging and discharging constraints of the energy storage system are as follows:
wherein alpha is more than 0 and less than or equal to 1 to represent the leakage rate of the energy storage system, q (t-1) represents the charge level of the energy storage system at the beginning of the time period t, and eta+And η-Respectively show the charging and discharging efficiency of the energy storage system,
and
respectively representing the total charge and the total discharge of the energy storage system in a time period t, and all end users
It is shown that,
and
representing the power supplied to and drawn from the energy storage system by end user n during time period t, Q, respectivelymRepresenting the maximum capacity of the energy storage system.
The electric energy trade price constraint is as follows:
where a (t) represents the electric energy trade price established by the aggregator, λ (t) represents the electric energy price of the energy center, and λ (t) ═ Φte(t)+t，φtAndtis a constant number of times, and is,
cn(t)maxrepresenting a maximum end user load less than the line power,
cn(t)minrepresenting the end user minimum load.
(2) The method comprises the steps that an end user preliminarily determines electric energy transaction amount which enables electricity consumption cost of each end user to be minimum according to electric energy transaction price preliminarily determined by an aggregator, energy balance constraint of the end user, uncertain photovoltaic power generation constraint and load energy consumption upper and lower limit constraint of the end user;
specifically, the end user's electricity cost, including the transaction cost with the aggregator and the user's satisfaction with electricity, may be expressed as:
Cn(t)＝-a(t)xn(t)+Sn(cn(t),dn(t))
wherein S isn(cn(t),dn(t))＝αndn(t)ln[(dn(t)+βn)/(cn(t)+βn)]Function representing end-user energy usage satisfaction, dn(t) nominal energy demand of end user, cn(t) actual energy consumption by the end-user, αnIndicating the priority of energy supply, alpha, to the user nn,βn＞0。
The constraints which need to be met by optimizing the electricity consumption cost of the end user comprise end user energy balance constraint, uncertain photovoltaic power generation constraint and user load energy consumption upper and lower limit constraint; wherein the energy balance constraint of the end user is: x is the number ofn(t)＝gn(t)-cn(t) in which gn(t) represents the supply of the photovoltaic power generation system to the end user n; the robust model of photovoltaic power generation uncertainty is represented as:
and is
Wherein
Representing the nominal supply of the photovoltaic power generation system to the end user n,nthe robust parameters are represented by a robust parameter,n(t) represents a maximum error value of the photovoltaic power generation system; the upper and lower limits of the load energy consumption constraint are denoted as cn(t)min≤cn(t)≤cn(t)max。
Giving the aggregator the established energy trade price a ═ a (1), a (2), …, a (H)]The terminal user n decides the optimal energy consumption
The electricity cost is minimized, and the optimal photovoltaic power generation amount of the terminal user n is expressed as
Thus, the optimal energy trading volume for end user n is represented as:
(3) the aggregator updates the electricity purchasing quantity and the electricity trading price according to the electricity trading quantity fed back by the terminal user, and finally obtains the optimal electricity purchasing quantity and the optimal electricity trading price which enable the aggregator to have the maximum benefits;
specifically, given an optimal amount of energy trades per end user
The aggregator decides an optimal strategy theta by optimizing a benefit function, electric energy supply constraint of an energy center, uncertain constraint of renewable energy power generation, charge and discharge constraint of an energy storage system and electric energy transaction price constraint*＝[a*,e*]To maximize the benefit, wherein a*＝[a*(1),a*(2),…,a*(H)]，e*＝[e*(1),e*(2),…,e*(H)]. By setting the termination criterion | | theta(r)-θ(r-1)||2/||θ(r)||2τ or less to achieve convergence of the distributed two-layer iterative algorithm, where θ(r)Representing the optimal strategy calculated by the aggregator at the r-th iteration, τ is a sufficiently small positive number. Through a series of two-way interaction processes, once the strategy of the aggregator converges to the optimal solution theta*All users have found their optimal policy X as well*Thus, the decentralized algorithm converges to the Stackelberg balancing strategy to maximize the benefits of the aggregator and minimize the cost of electricity usage per user.
(4) The terminal user updates the electric energy transaction amount according to the optimal electric energy transaction price, and finally the optimal electric energy transaction amount which enables the electricity consumption cost of each terminal user to be minimum is obtained;
(5) the aggregator acquires electric energy from the energy center according to the optimal electric energy purchasing quantity, and the terminal user conducts electric energy transaction with the energy storage system according to the optimal electric energy transaction quantity.
The implementation process of the energy transaction method is distributed, the bidirectional interaction process between the aggregator and the terminal user can be completely realized through the current bidirectional communication technology, the private information of all users can be protected, the calculation efficiency can be improved, and the energy transaction method can be applied to solving the energy management problem of a large-scale ocean island microgrid. Most importantly, the distributed periodic energy trading framework provided by the invention can effectively solve the problems of sufficient energy supply and insufficient energy supply of the ocean island microgrid, ensure the reliable economic operation of the island microgrid system and preferentially meet the power utilization requirements of strategic users.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (7)
1. A distributed periodic energy trading method for an ocean island microgrid system is characterized in that the ocean island microgrid system comprises the following steps: the system comprises an energy center, an aggregator, an energy storage system and an end user;
the energy center is used for storing energy periodically transported from the continent to the ocean island and electric energy generated by power generation of renewable energy on the ocean island and providing electric energy for the load of the island microgrid;
the aggregator is used for determining the electric energy acquired from an energy center and the electric energy transaction price of the end user according to the electric energy transaction demand of the end user, and scheduling the charging and discharging amount of the energy storage system;
the energy storage system is used for acquiring electric energy from the energy center according to the scheduling of the aggregator and providing the acquired electric energy for the terminal user;
the terminal user is used for determining the electric energy transaction amount obtained from the energy storage system according to the electric energy transaction price of the aggregator;
the distributed periodic energy trading method for the ocean island microgrid system comprises the following steps:
(1) the aggregator preliminarily obtains the electricity purchasing quantity and the electric energy transaction price which enable the aggregator to be most beneficial according to the electric energy supply constraint of the energy center, the uncertain constraint of renewable energy power generation, the charge-discharge constraint of the energy storage system and the electric energy transaction price constraint;
(2) the terminal user preliminarily determines the electric energy transaction amount which enables the electricity consumption cost of each terminal user to be minimum according to the electric energy transaction price preliminarily determined by the aggregator, the energy balance constraint of the terminal user, the uncertain photovoltaic power generation constraint and the upper and lower limit constraints of the load energy consumption of the terminal user;
(3) the aggregator updates the electricity purchasing quantity and the electricity trading price according to the electricity trading quantity fed back by the terminal user, and finally obtains the optimal electricity purchasing quantity and the optimal electricity trading price which enable the aggregator to have the maximum benefit;
(4) the terminal user updates the electric energy transaction amount according to the optimal electric energy transaction price, and finally the optimal electric energy transaction amount which enables the electricity consumption cost of each terminal user to be minimum is obtained;
(5) and the aggregator acquires electric energy from an energy center according to the optimal electricity purchasing quantity, and the terminal user carries out electric energy transaction with an energy storage system according to the optimal electric energy transaction quantity.
2. The decentralized periodic energy transaction method according to claim 1, wherein the energy supply constraint of the energy center is:
wherein e (t) represents the amount of electric energy purchased by the aggregator from the energy center for time period t, L (t)maxRepresenting the maximum load that the energy center can supply during the time period t, EtRepresenting energy transported to the ocean island, ErRepresenting the total amount of renewable energy power generation on the ocean island in one scheduling period, and representing the time period of one scheduling period as
H represents the number of time segments of a scheduling periodAnd the dispatching cycle refers to the transportation cycle of the energy from the continent to the ocean island.
3. The decentralized periodic energy trading method according to claim 1, wherein said renewable energy generation uncertainty constraint is expressed as:
wherein,
representing the nominal total amount of renewable energy generation during a scheduling period,rthe robust parameters are represented by a robust parameter,rrepresenting the maximum error value of renewable energy power generation.
4. The distributed periodic energy trading method of claim 1, wherein the charging and discharging constraints of the energy storage system are as follows:
wherein alpha is more than 0 and less than or equal to 1 to represent the leakage rate of the energy storage system, q (t-1) represents the charge level of the energy storage system at the beginning of the time period t, and eta+And η-Respectively show the charging and discharging efficiency of the energy storage system,
and
respectively representing the total charge and the total discharge of the energy storage system in a time period t, and all end users
It is shown that,
and
representing the power supplied to and drawn from the energy storage system by end user n during time period t, Q, respectivelymRepresents a maximum capacity of the energy storage system; e (t) represents the amount of electrical energy purchased by the aggregator from the energy center for time period t.
5. The decentralized periodic energy transaction method according to claim 1, wherein said electric energy transaction price constraint is:
where a (t) represents the electric energy trade price established by the aggregator, λ (t) represents the electric energy price of the energy center, and λ (t) ═ Φte(t)+t，φtAndtis a constant number of times, and is,
cn(t)maxrepresenting a maximum end user load less than the line power,
cn(t)minrepresents the end user minimum load; e (t) represents the amount of electrical energy purchased by the aggregator from the energy center for time period t; alpha is alphanRepresents the energy supply priority of the user n; dn(t) is the nominal energy demand of the end user;
representing the end user.
6. The decentralized periodic capacity trading method according to claim 1, wherein the benefit R of said aggregator in one scheduling period is:
wherein x isn(t) represents the electric energy transaction amount of the end user n and the energy storage system; h represents the time period number of a dispatching cycle, a (t) represents the electric energy trading price set by the aggregator; n represents the number of end users; λ (t) represents an energy price of the energy center; e (t) represents the amount of electrical energy purchased by the aggregator from the energy center for time period t.
7. The decentralized periodic energy trading method according to claim 1, wherein the energy balance constraint of the end user is:
xn(t)＝gn(t)-cn(t)
wherein, gn(t) represents the supply of the photovoltaic power generation system to the end user n, cn(t) is the actual power consumption of the end user;
the photovoltaic power generation uncertainty constraint is expressed as:
wherein,
representing the nominal supply of the photovoltaic power generation system to the end user n,nthe robust parameters are represented by a robust parameter,n(t) represents a maximum error value of the photovoltaic power generation system;
the upper and lower limits of the load energy consumption of the terminal user are constrained as follows:
cn(t)min≤cn(t)≤cn(t)max
the electric energy use cost C of the terminal usern(t) is：
Cn(t)＝-a(t)xn(t)+Sn(cn(t),dn(t))
Wherein S isn(cn(t),dn(t))＝αndn(t)ln[(dn(t)+βn)/(cn(t)+βn)]Function representing the end user satisfaction of electric energy usage, dn(t) is the nominal power demand, α, of the end usernIndicating the priority of power supply, alpha, to the user nn,βn＞0；xn(t) represents the electric energy transaction amount of the end user n and the energy storage system; and a (t) represents the electric energy transaction price established by the aggregator.
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