CN111882105A - Microgrid group with shared energy storage system and day-ahead economic optimization scheduling method thereof - Google Patents
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Abstract
The invention discloses a micro-grid group with a shared energy storage system and a day-ahead economic optimization scheduling method thereof, wherein the method comprises the following steps: step 1, establishing an operation model of each part in a microgrid group containing a shared energy storage system; step 2, based on the step 1, aiming at the lowest operation cost of the micro-grid group system, introducing system operation constraint, and establishing a day-ahead economic optimization scheduling model of the micro-grid group; and 3, acquiring the operation cost coefficient and the operation limit value of each device in the microgrid group, solving the day-ahead economic optimization scheduling model based on the steps 1 and 2, and determining a day-ahead scheduling scheme of the microgrid group system. According to the method, a micro-grid group system comprising a shared energy storage system is considered, each micro-grid can realize bidirectional energy flow with the shared energy storage system through a connecting line, so that energy storage and interaction of energy among different micro-grids are realized, the consumption of renewable energy sources is effectively realized, the effects of peak clipping and valley filling are realized, the energy utilization efficiency is improved, and the electricity utilization cost is reduced.
Description
Technical Field
The invention belongs to the technical field of operation optimization of energy systems, and particularly relates to a micro-grid group with a shared energy storage system and a day-ahead economic optimization scheduling method thereof.
Background
In order to cope with increasingly severe climate change, some countries set their own carbon emission reduction targets. Renewable energy is considered as an important way to reduce carbon emissions, and accordingly, the popularity of renewable energy has increased significantly in the last decade. The high permeability of renewable energy sources will present challenges to network operators due to their fluctuating nature. Therefore, in order to alleviate the fluctuation of the renewable energy output and satisfy the power balance, an energy storage system is widely adopted at present. Despite the declining price of batteries, the price and service life of batteries remain considerable. Therefore, it is desirable to explore ways to effectively utilize energy storage systems to accommodate the ever-increasing demand for renewable energy.
Much research has focused on the shared use of energy storage systems. However, there has been much research focused on the control and pricing of energy exchange between energy storage systems and energy consumers, with less concern for the trading of electrical energy between consumers through a commonly connected energy storage system. According to the modular bidirectional converter apparatus, electric energy transactions between different users can be realized using a plurality of individual AC/DC conversion modules and a shared DC/DC conversion module. Due to the power flow controllability of the AC/DC module, electric power transaction among participants is controllable, and electricity purchasing and selling charging can be realized by adding a metering unit on the AC/DC module. Therefore, a method for economically and optimally scheduling a microgrid cluster comprising a shared energy storage system in the future considering P2P trading needs to be provided.
Disclosure of Invention
The purpose of the invention is as follows: in order to reduce the influence of the fluctuation and uncertainty of the output of the renewable energy on a microgrid group system, promote the consumption of the renewable energy and realize the functions of peak clipping and valley filling, the invention provides a microgrid group comprising a shared energy storage system and a day-ahead economic optimization scheduling method of the microgrid group comprising the shared energy storage system so as to realize the optimized operation of the microgrid group system.
The technical scheme is as follows: in order to realize the purpose, the invention adopts the following technical scheme:
a micro-grid group with a shared energy storage system comprises an active power distribution network, a micro-grid group and the shared energy storage system;
each micro-grid in the micro-grid group realizes power interaction with the active power distribution network and the shared energy storage system through a connecting line, and when electric power generated by new energy power generation in the micro-grid is larger than electric load, electricity is sold to the active power distribution network or the shared energy storage system, so that power balance of an electric bus is met; otherwise, purchasing electricity to the active power distribution network or the shared energy storage system; each micro grid is connected to a direct current bus of the shared energy storage system through a circuit breaker and an AC/DC conversion module, and then is connected with the battery system through the DC/DC conversion module and a DC isolator, wherein the AC/DC conversion module and the DC/DC conversion module are both bidirectional converters.
The invention provides a day-ahead economic optimization scheduling method for a microgrid cluster with a shared energy storage system, which comprises the following steps:
and 3, acquiring the operation cost coefficient and the operation limit value of each device in the microgrid group, solving the day-ahead economic optimization scheduling model based on the steps 1 and 2, and determining a day-ahead scheduling scheme of the microgrid group system.
In the step 1, the operation models of all parts in the microgrid group with the shared energy storage system comprise an operation model of renewable energy power generation, an operation model of the shared energy storage system and an operation model of microgrid power interaction with an active power distribution network, and the specific flow is as follows:
step 101, an operation model of renewable energy power generation:
the renewable energy power generation in each microgrid mainly comprises two forms of photovoltaic power generation and wind power generation, and the relationship between the operation and maintenance cost and the power generation power of the renewable energy power generation in each microgrid is as follows:
wherein, T represents a scheduling period, and Δ T represents a scheduling time resolution;
operating and maintaining cost for new energy power generation of the microgrid i;
representing the operation and maintenance cost coefficient of the photovoltaic/wind turbine;
representing the generated power of the photovoltaic/fan of the micro-grid i at the moment t;
step 102, sharing an operation model of the energy storage system:
the electricity purchase cost of each micro-grid from the shared energy storage system is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the micro-grid i from the shared energy storage system;
the electricity purchasing/selling price of the micro-grid i to the shared energy storage system at the time t is represented;
the power of electricity purchased/sold by the micro-grid i to the shared energy storage system at the moment t is represented;
the electricity purchasing price/electricity selling price of each microgrid to the shared energy storage system is determined by the following formulas (3) to (5):
in the formula (I), the compound is shown in the specification,
the electricity purchasing/selling reference electricity price of the micro-grid i to the shared energy storage system at the time t is represented;
representing the electric load power of the microgrid i at the time t;
the ratio of the load power of the microgrid i at the moment t to the power generated by the renewable energy source is expressed,
is composed of
Normalized to the interval [ -1,1 [ ]]Setting the electricity purchasing price of the slave shared energy storage system to be not higher than the electricity purchasing price of the slave active power distribution network at each moment, setting the electricity selling price of the slave shared energy storage system to be not lower than the electricity selling price of the master active power distribution network, and setting the electricity purchasing price of the slave shared energy storage system to be not lower than the electricity selling price of the slave shared energy storage system;
the direct current bus inside the shared energy storage system must satisfy electric power balance:
in the formula (I), the compound is shown in the specification,
the value of the power purchased/sold by the microgrid i to the shared energy storage system at the time t is transmitted to the direct current bus,
the value of the charging and discharging power of the battery in the shared energy storage system transmitted to the direct current bus is represented;
due to the capacity limitation of the tie line and the AC/DC converter, the interactive power value of each microgrid and the shared energy storage system is limited by upper and lower limits, and meanwhile, at each moment, the electricity purchasing/selling behaviors of each microgrid and the shared energy storage system cannot occur simultaneously, as shown in formulas (7) to (9):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the state of electricity purchasing/electricity selling of the micro-grid i to the shared energy storage system at the time t is represented;
representing an upper power limit for purchasing/selling power to the shared energy storage system;
due to the capacity limitations of the battery and the DC/DC converter, there is an upper limit constraint on the charging and discharging power value of the battery inside the shared energy storage system, and at the same time, there is a lower limit constraint on the power value in order to prevent unnecessary battery loss, and in addition, at each moment, the charging and discharging behaviors of the battery cannot occur simultaneously, as shown in equations (10) to (12):
in the formula (I), the compound is shown in the specification,
a variable of 0 to 1, representing the charge/discharge state of the battery at time t;
representing the charge/discharge power of the battery at time t,
represents the upper/lower power limit for battery charging/discharging;
in order to reduce the loss of the battery and further ensure the service life of the battery, the charge-discharge cycle power constraint of the battery is required to be added:
in the formula (I), the compound is shown in the specification,
represents the maximum charge-discharge cycle power of the battery;
in addition, in order to ensure the sustainable development of the scheduling strategy, the energy of the battery is required to be equal at the beginning and the end of each scheduling period, as formulas (14) to (16):
in the formula (I), the compound is shown in the specification,
representing the energy of the battery inside the shared energy storage system at time t,
represents a minimum/maximum value of battery energy; sigmaESSIndicating the self-discharge rate of the battery.
Because the bidirectional converter inside the shared energy storage system has certain power loss, the efficiency constraint of each device needs to be added:
in the formula etaESS,DC,ACRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from DC to ACESS,AC,DCRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from AC to DCESS,disRepresenting the efficiency, η, of the DC/DC converter when the battery is dischargedESS,chIndicating DC/DC converter during battery chargingThe efficiency of (c);
103, an operation model of power interaction of the micro-grid and the active power distribution network is as follows:
the electricity purchasing cost of each micro-grid from the active power distribution network is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the microgrid i from the active power distribution network;
the electricity purchasing/selling price of the micro-grid i to the active power distribution network at the time t is represented;
the power of electricity purchased/sold from the microgrid i to the active power distribution network at the moment t is represented;
due to the capacity limitation of the connecting line and the transformer, the interactive power value of each microgrid and the active power distribution network is restricted by upper and lower limits, and meanwhile, the electricity purchasing/selling behaviors of each microgrid and the active power distribution network cannot occur simultaneously at each moment, as shown in formulas (22) to (24):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the electricity purchasing/selling state of the microgrid i to the active power distribution network at the moment t is represented;
represents the upper limit of power purchased/sold to the active distribution grid.
The process for establishing the day-ahead economic optimization scheduling model of the microgrid group with the shared energy storage system in the step 2 is as follows:
step 201, establishing an optimization model objective function:
the optimized objective function is to minimize the total operation cost of the microgrid group, wherein the operation and maintenance cost of the wind turbine and the photovoltaic, the electricity purchasing cost from the active power distribution network, and the electricity purchasing cost from the shared energy storage system are as follows:
in the formula, Cost represents the total operation Cost of the microgrid group; ciRepresenting the operating cost of the microgrid i;
respectively representing the new energy power generation operation maintenance cost of the microgrid i, the electricity purchasing cost from an active power distribution network and the electricity purchasing cost from a shared energy storage system, wherein the calculation methods are respectively shown as formulas (1), (21), (2) to (5);
step 202, establishing an optimization model constraint condition:
1) microgrid electric power balance constraint:
electric power balance must be satisfied inside each microgrid:
2) and (3) sharing electric power balance constraint of the direct current bus of the energy storage system:
the electric power balance relation of the direct current bus of the shared energy storage system satisfies an equation (6);
3) purchasing upper and lower limits of power selling power to the active power distribution network:
the restriction of purchasing and selling the power of the active power distribution network satisfies the formulas (22) - (24);
4) and (3) purchasing and selling power upper and lower limits of the energy storage system to be restricted:
the upper and lower limits of the power purchasing and selling of the shared energy storage system are constrained to satisfy the formulas (7) - (9);
5) the transaction of the shared energy storage system and the active power distribution network through the microgrid is prevented:
for economic and safety reasons, the microgrid is not allowed to sell electric energy purchased from the active power distribution network to the shared energy storage system or to sell electric energy purchased from the shared energy storage system to the active power distribution network at the same time:
6) and (3) battery charging and discharging power constraint of the shared energy storage system:
the battery charge and discharge power constraint of the shared energy storage system satisfies the formulas (10) - (12);
7) and (3) battery charge-discharge cycle power constraint of the shared energy storage system:
the battery charge-discharge cycle power constraint of the shared energy storage system satisfies the formula (13);
8) and (3) battery energy constraint of the shared energy storage system:
the shared energy storage system battery energy constraint satisfies equations (14) - (16);
9) energy conversion efficiency constraint of the shared energy storage system:
the shared energy storage system energy conversion efficiency constraint satisfies equations (17) - (20).
And 3, solving the day-ahead economic Optimization scheduling model, wherein decision variables comprise the state and power of electricity purchased from each microgrid to the active power distribution network, the state and power of electricity purchased from each microgrid to the shared energy storage system, the charge-discharge state and power of a battery of the shared energy storage system and the energy of the battery of the shared energy storage system, and after acquiring the running cost coefficient and the running limit value of each device in the microgrid group, solving the day-ahead economic Optimization scheduling model by using IBM ILOG CPLEX Optimization Studio in combination with MATLAB to determine a day-ahead scheduling scheme of the microgrid group system.
The day-ahead economic optimization scheduling model of the microgrid group with the shared energy storage system has a scheduling period of 24 hours, namely T is 24.
According to the day-ahead economic optimization scheduling model of the microgrid group with the shared energy storage system, the scheduling time resolution is 1 hour, namely delta t is 1.
Has the advantages that: compared with the prior art, the invention has the following advantages:
the invention provides a micro-grid group operation optimization method with a shared energy storage system. A micro-grid group comprising a shared energy storage system is established, the micro-grid can realize bidirectional energy flow with the shared energy storage system through a connecting line, so that energy storage and interaction of energy among different micro-grids are realized, the consumption of renewable energy sources is effectively realized, the effects of peak clipping and valley filling are realized, the energy utilization efficiency is improved, and the electricity utilization cost is reduced. Therefore, the operation cost of the micro-grid group system can be obviously reduced and the day-ahead economic optimization scheduling of the micro-grid group can be realized by optimizing the charge-discharge state and power of the shared energy storage system and the electricity purchasing and selling strategy of the micro-grid.
Drawings
FIG. 1 is a microgrid group architecture including a shared energy storage system;
FIG. 2 is a configuration of a shared energy storage system;
FIGS. 3(a) - (d) are diagrams of the electrical power balance of each microgrid in an embodiment of the present invention;
FIG. 4 is a diagram illustrating the power balance of the DC bus of the shared energy storage system according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating the variation of energy in the batteries of the shared energy storage system according to an embodiment of the present invention;
fig. 6 is a cost diagram of each microgrid in an embodiment of the present invention.
Fig. 7 is a cost diagram of each microgrid when a shared energy storage system is not added in the embodiment of the present invention.
Detailed Description
The technical solution of the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.
The invention will be explained in more detail below with reference to the drawings and examples. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention and not to limit the present invention.
The overall structure of the microgrid group system with shared energy storage researched by the invention is shown in fig. 1. The microgrid adopts a bus type structure, and each microgrid has respective electric load inside and comprises new energy power generation equipment such as photovoltaic power generation equipment and draught fans. Meanwhile, each micro-grid can realize power interaction with the active power distribution network and the shared energy storage system through tie lines respectively. Bidirectional power flow exists among the micro-grid, the active power distribution network and the shared energy storage system, and when electric power generated by new energy power generation in the micro-grid is larger than an electric load, electricity can be sold to the active power distribution network or the shared energy storage system, so that power balance of an electric bus is met; otherwise, electricity can be purchased from the active power distribution network or the shared energy storage system.
The structure of the shared energy storage system as a key device in the microgrid group is shown in fig. 2. Each microgrid is connected to a direct-current bus of the shared energy storage system through a circuit breaker and an AC/DC conversion module, and then is connected with the battery system through the DC/DC conversion module and a DC isolator. The AC/DC conversion module and the DC/DC conversion module which are responsible for energy conversion are both bidirectional converters. The operation mode of the shared energy storage system is as follows: firstly, each microgrid transmits the power value required by or to be consumed to a direct current bus according to the power shortage or the power surplus, so that the total power shortage or the power surplus of the microgrid group is obtained, and then the charging and discharging strategy and the power of the battery are determined so as to maintain the power balance of the direct current bus of the shared energy storage system. Therefore, in addition to charging and discharging of the battery system of the shared energy storage system, indirect power interaction can be achieved among the micro-grids through the AC/DC conversion module and the direct-current bus, and therefore flexibility of a scheduling strategy is improved.
The invention provides a day-ahead economic optimization scheduling method for a microgrid cluster with a shared energy storage system, which comprises the following steps:
and 3, acquiring the operation cost coefficient and the operation limit value of each device in the microgrid group, solving the day-ahead economic optimization scheduling model based on the steps 1 and 2, and determining a day-ahead scheduling scheme of the microgrid group system.
The operation model of each part in the microgrid group with the shared energy storage system in the step 1 comprises three aspects of an operation model of renewable energy power generation, an operation model of the shared energy storage system and an operation model of microgrid and active power distribution network power interaction. The specific process of the step 1 is as follows:
step 101. operation model of renewable energy power generation
Renewable energy power generation in each microgrid mainly comprises two forms of photovoltaic power generation and wind power generation. The relationship between the operation and maintenance cost of renewable energy power generation and the generated power in each microgrid is as follows:
wherein, T represents a scheduling period, and Δ T represents a scheduling time resolution;
operating and maintaining cost for new energy power generation of the microgrid i;
representing the operation and maintenance cost coefficient of the photovoltaic/wind turbine;
representing the generated power of the photovoltaic/fan of the micro-grid i at the moment t;
step 102, sharing an operation model of the energy storage system:
the electricity purchase cost of each micro-grid from the shared energy storage system is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the micro-grid i from the shared energy storage system;
the electricity purchasing/selling price of the micro-grid i to the shared energy storage system at the time t is represented;
the power of electricity purchased/sold by the micro-grid i to the shared energy storage system at the moment t is represented;
the electricity purchasing price/electricity selling price of each microgrid to the shared energy storage system is determined by the following formulas (3) to (5):
in the formula (I), the compound is shown in the specification,
the electricity purchasing/selling reference electricity price of the micro-grid i to the shared energy storage system at the time t is represented;
representing the electric load power of the microgrid i at the time t;
the ratio of the load power of the microgrid i at the moment t to the power generated by the renewable energy source is expressed,
is composed of
Normalized to the interval [ -1,1 [ ]]Setting the electricity purchasing price of the slave shared energy storage system to be not higher than the electricity purchasing price of the slave active power distribution network at each moment, setting the electricity selling price of the slave shared energy storage system to be not lower than the electricity selling price of the master active power distribution network, and setting the electricity purchasing price of the slave shared energy storage system to be not lower than the electricity selling price of the slave shared energy storage system;
the direct current bus inside the shared energy storage system must satisfy electric power balance:
in the formula (I), the compound is shown in the specification,
the value of the power purchased/sold by the microgrid i to the shared energy storage system at the time t is transmitted to the direct current bus,
the value of the charging and discharging power of the battery in the shared energy storage system transmitted to the direct current bus is represented;
due to the capacity limitation of the tie line and the AC/DC converter, the interactive power value of each microgrid and the shared energy storage system is limited by upper and lower limits, and meanwhile, at each moment, the electricity purchasing/selling behaviors of each microgrid and the shared energy storage system cannot occur simultaneously, as shown in formulas (7) to (9):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the state of electricity purchasing/electricity selling of the micro-grid i to the shared energy storage system at the time t is represented;
representing an upper power limit for purchasing/selling power to the shared energy storage system;
due to the capacity limitations of the battery and the DC/DC converter, there is an upper limit constraint on the charging and discharging power value of the battery inside the shared energy storage system, and at the same time, there is a lower limit constraint on the power value in order to prevent unnecessary battery loss, and in addition, at each moment, the charging and discharging behaviors of the battery cannot occur simultaneously, as shown in equations (10) to (12):
in the formula (I), the compound is shown in the specification,
a variable of 0 to 1, representing the charge/discharge state of the battery at time t;
representing the charge/discharge power of the battery at time t,
represents the upper/lower power limit for battery charging/discharging;
in order to reduce the loss of the battery and further ensure the service life of the battery, the charge-discharge cycle power constraint of the battery is required to be added:
in the formula (I), the compound is shown in the specification,
represents the maximum charge-discharge cycle power of the battery;
in addition, in order to ensure the sustainable development of the scheduling strategy, the energy of the battery is required to be equal at the beginning and the end of each scheduling period, as formulas (14) to (16):
in the formula (I), the compound is shown in the specification,
representing the energy of the battery inside the shared energy storage system at time t,
to representMinimum/maximum battery energy; sigmaESSIndicating the self-discharge rate of the battery.
Because the bidirectional converter inside the shared energy storage system has certain power loss, the efficiency constraint of each device needs to be added:
in the formula etaESS,DC,ACRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from DC to ACESS,AC,DCRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from AC to DCESS,disRepresenting the efficiency, η, of the DC/DC converter when the battery is dischargedESS,chRepresents the efficiency of the DC/DC converter when the battery is charged;
103, an operation model of power interaction of the micro-grid and the active power distribution network is as follows:
the electricity purchasing cost of each micro-grid from the active power distribution network is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the microgrid i from the active power distribution network;
the electricity purchasing/selling price of the micro-grid i to the active power distribution network at the time t is represented;
the power of electricity purchased/sold from the microgrid i to the active power distribution network at the moment t is represented;
due to the capacity limitation of the connecting line and the transformer, the interactive power value of each microgrid and the active power distribution network is restricted by upper and lower limits, and meanwhile, the electricity purchasing/selling behaviors of each microgrid and the active power distribution network cannot occur simultaneously at each moment, as shown in formulas (22) to (24):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the electricity purchasing/selling state of the microgrid i to the active power distribution network at the moment t is represented;
represents the upper limit of power purchased/sold to the active distribution grid.
The process for establishing the day-ahead economic optimization scheduling model of the microgrid group with the shared energy storage system in the step 2 is as follows:
step 201, establishing an optimization model objective function:
the optimized objective function is to minimize the total operation cost of the microgrid group, wherein the operation and maintenance cost of the wind turbine and the photovoltaic, the electricity purchasing cost from the active power distribution network, and the electricity purchasing cost from the shared energy storage system are as follows:
in the formula, Cost represents the total operation Cost of the microgrid group; ciRepresenting the operating cost of the microgrid i;
respectively representing the new energy power generation operation maintenance cost of the microgrid i, the electricity purchasing cost from an active power distribution network and the electricity purchasing cost from a shared energy storage system, wherein the calculation methods are respectively shown as formulas (1), (21), (2) to (5);
step 202, establishing an optimization model constraint condition:
1) microgrid electric power balance constraint:
electric power balance must be satisfied inside each microgrid:
2) and (3) sharing electric power balance constraint of the direct current bus of the energy storage system:
the electric power balance relation of the direct current bus of the shared energy storage system satisfies an equation (6);
3) purchasing upper and lower limits of power selling power to the active power distribution network:
the restriction of purchasing and selling the power of the active power distribution network satisfies the formulas (22) - (24);
4) and (3) purchasing and selling power upper and lower limits of the energy storage system to be restricted:
the upper and lower limits of the power purchasing and selling of the shared energy storage system are constrained to satisfy the formulas (7) - (9);
5) the transaction of the shared energy storage system and the active power distribution network through the microgrid is prevented:
for economic and safety reasons, the microgrid is not allowed to sell electric energy purchased from the active power distribution network to the shared energy storage system or to sell electric energy purchased from the shared energy storage system to the active power distribution network at the same time:
6) and (3) battery charging and discharging power constraint of the shared energy storage system:
the battery charge and discharge power constraint of the shared energy storage system satisfies the formulas (10) - (12);
7) and (3) battery charge-discharge cycle power constraint of the shared energy storage system:
the battery charge-discharge cycle power constraint of the shared energy storage system satisfies the formula (13);
8) and (3) battery energy constraint of the shared energy storage system:
the shared energy storage system battery energy constraint satisfies equations (14) - (16);
9) energy conversion efficiency constraint of the shared energy storage system:
the shared energy storage system energy conversion efficiency constraint satisfies equations (17) - (20).
And 3, solving the day-ahead economic Optimization scheduling model, wherein decision variables comprise the electricity purchasing state and power of each microgrid to the active power distribution network, the electricity purchasing state and power of each microgrid to the shared energy storage system, the charge-discharge state and power of a battery of the shared energy storage system, the energy of the battery of the shared energy storage system and the like, and after acquiring the running cost coefficient and the running limit value of each device in the microgrid group, solving the day-ahead economic Optimization scheduling model by using IBM ILOG CPLEX Optimization Studio in combination with MATLAB to determine a day-ahead scheduling scheme of the microgrid group system.
According to the day-ahead economic optimization scheduling model of the microgrid cluster with the shared energy storage system, the scheduling period is 24 hours, namely T is 24, and the scheduling time resolution is 1 hour, namely delta T is 1.
The operating parameters of the system are shown in table 1.
TABLE 1 System operating parameters
The micro-grid group system adopts a time-of-use electricity price pricing mode. Wherein the peak period time is 08:00-11:00 and 18:00-23:00, the flat period time is 07:00-08:00 and 11:00-18:00, the valley period time is 23:00-07:00, and the real-time trading electricity price is shown in table 2. And the new energy of the power grid adopts 0.34 yuan/(kWh) of power price for power generation and grid surfing.
TABLE 2 real-time trading electricity prices
In the embodiment, the battery capacity of the shared energy storage system is 3000kWh, and 4 micro grids are connected to the shared energy storage system to form a micro grid group. The results of the optimization are shown in fig. 3-6.
As can be seen from fig. 3, for peak periods 08:00-11:00 and 18:00-23:00 of electricity prices, the vast majority of electrical loads are satisfied by purchasing electricity to the shared energy storage system, rather than the active distribution grid where electricity prices are expensive; in the usual period of the electricity price, most of the electricity load is satisfied by purchasing electricity to the active power distribution network due to the relatively low price; during the off-peak period of the electricity price, because the wind power generation output is often more, the electricity needs to be sold when the supply is over demand, most of the power is sold to the shared energy storage system, but because the capacity of the shared energy storage system is limited, a part of surplus power of the microgrid 1 is sold to the active power distribution network. The reason why the microgrid 1 sells electricity to the active power distribution network instead of other microgrids is that the price of electricity sold by the microgrid 1 to the shared energy storage system is lowest in the period of time, so that surplus power is sold to the active power distribution network by the microgrid 1, and the whole microgrid group can obtain the maximum economic benefit.
As can be seen from fig. 4 to 5, in the time period 23:00 when the power generation of each microgrid renewable energy source is greater than the electrical load, 7:00 days next time, the batteries of the shared energy storage system are charged; and the batteries of the shared energy storage system are discharged when the electricity price of the active power distribution network is higher at 08:00-11:00 and 18:00-21: 00. Therefore, the shared energy storage system is used, so that the peak clipping and valley filling effects can be achieved, the consumption of renewable energy can be realized, and the electricity utilization cost is reduced. In addition, at 13:00-16:00 and 21:00-23:00, due to the fact that renewable energy sources of the microgrid 4 generate more power, power needs to be sold to meet electric power balance, and other microgrids still need to purchase power, at this time, the microgrid 4 does not need to select an active power distribution network with lower power price of the upper power grid to sell power, or need not charge batteries, and power can be sold to the microgrid 2 and the microgrid 1 indirectly through a direct-current bus in the shared energy storage system. Thus, the energy transmission efficiency is improved, the battery loss is reduced, and the electricity consumption cost is reduced. Similarly, in the selection of the microgrid, the algorithm automatically selects the microgrid with the lowest electricity purchasing cost from the shared energy storage system to perform power interaction.
As can be seen from fig. 6, the microgrid 3 with a higher load has a higher electricity consumption cost due to more electricity purchased from the active power distribution network; and the micro-grid 4 with more renewable energy sources sells more electricity to the shared energy storage system, so that more profits can be obtained.
In contrast, in the case of a shared-nothing energy storage system, the cost of each microgrid after optimization is shown in fig. 7.
Under the scene, the surplus power of each microgrid can only be sold to the active power distribution network, and the shortage of power can only be bought from the active power distribution network. As can be seen from fig. 7, in the case of the shared-nothing energy storage system, the total electricity consumption cost is 4070.6475 yuan, and in the case of the shared energy storage system, the total electricity consumption cost is reduced to 3360.8191 yuan, which saves 699.8284 yuan altogether, and the cost saving accounts for 17.23%. For the microgrid 4 with more renewable energy power generation, the electricity selling profit is improved from 402.2410 yuan to 557.6242 yuan, and is improved from 155.3832 yuan, namely 38.63%. Therefore, the shared energy storage system plays an important role in the operation of the whole microgrid group system, and the power utilization cost can be greatly reduced.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited by the foregoing examples, which are provided to illustrate the principles of the invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention, which is also intended to be covered by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A micro-grid group with a shared energy storage system comprises an active power distribution network, a micro-grid group and the shared energy storage system; the method is characterized in that:
each micro-grid in the micro-grid group realizes power interaction with the active power distribution network and the shared energy storage system through a connecting line, and when electric power generated by new energy power generation in the micro-grid is larger than electric load, electricity is sold to the active power distribution network or the shared energy storage system, so that power balance of an electric bus is met; otherwise, purchasing electricity to the active power distribution network or the shared energy storage system; each micro grid is connected to a direct current bus of the shared energy storage system through a circuit breaker and an AC/DC conversion module, and then is connected with the battery system through the DC/DC conversion module and a DC isolator, wherein the AC/DC conversion module and the DC/DC conversion module are both bidirectional converters.
2. A day-ahead economic optimization scheduling method for a micro-grid group with a shared energy storage system is characterized by comprising the following steps: the method comprises the following steps:
step 1, establishing an operation model of each part in a microgrid group containing a shared energy storage system;
step 2, based on the step 1, aiming at the lowest operation cost of the micro-grid group system, introducing system operation constraint, and establishing a micro-grid group day-ahead economic optimization scheduling model containing a shared energy storage system;
and 3, acquiring the operation cost coefficient and the operation limit value of each device in the microgrid group, solving the day-ahead economic optimization scheduling model based on the steps 1 and 2, and determining a day-ahead scheduling scheme of the microgrid group system.
3. The method of claim 2, wherein the method comprises: in the step 1, the operation models of all parts in the microgrid group with the shared energy storage system comprise an operation model of renewable energy power generation, an operation model of the shared energy storage system and an operation model of microgrid power interaction with an active power distribution network, and the specific flow is as follows:
step 101, an operation model of renewable energy power generation:
the renewable energy power generation in each microgrid mainly comprises two forms of photovoltaic power generation and wind power generation, and the relationship between the operation and maintenance cost and the power generation power of the renewable energy power generation in each microgrid is as follows:
wherein, T represents a scheduling period, and Δ T represents a scheduling time resolution;
operating and maintaining cost for new energy power generation of the microgrid i;
representing the operation and maintenance cost coefficient of the photovoltaic/wind turbine;
representing the generated power of the photovoltaic/fan of the micro-grid i at the moment t;
step 102, sharing an operation model of the energy storage system:
the electricity purchase cost of each micro-grid from the shared energy storage system is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the micro-grid i from the shared energy storage system;
indicating microgrid i atthe electricity purchasing price/electricity selling price of the shared energy storage system is reached at the moment t;
the power of electricity purchased/sold by the micro-grid i to the shared energy storage system at the moment t is represented;
the electricity purchasing price/electricity selling price of each microgrid to the shared energy storage system is determined by the following formulas (3) to (5):
in the formula (I), the compound is shown in the specification,
the electricity purchasing/selling reference electricity price of the micro-grid i to the shared energy storage system at the time t is represented;
representing the electric load power of the microgrid i at the time t;
the ratio of the load power of the microgrid i at the moment t to the power generated by the renewable energy source is expressed,
is composed of
Normalized to the interval [ -1,1 [ ]]The later value, at the same time, the electricity purchase price of the slave sharing energy storage system is set not higher than the electricity purchase price of the slave active power distribution network at each moment, and the sale to the sharing energy storage system is carried outThe electricity price is not lower than the electricity selling price of the active power distribution network, and the electricity purchasing price of the secondary sharing energy storage system is not lower than the electricity selling price of the secondary sharing energy storage system;
the direct current bus inside the shared energy storage system must satisfy electric power balance:
in the formula (I), the compound is shown in the specification,
the value of the power purchased/sold by the microgrid i to the shared energy storage system at the time t is transmitted to the direct current bus,
the value of the charging and discharging power of the battery in the shared energy storage system transmitted to the direct current bus is represented;
due to the capacity limitation of the tie line and the AC/DC converter, the interactive power value of each microgrid and the shared energy storage system is limited by upper and lower limits, and meanwhile, at each moment, the electricity purchasing/selling behaviors of each microgrid and the shared energy storage system cannot occur simultaneously, as shown in formulas (7) to (9):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the state of electricity purchasing/electricity selling of the micro-grid i to the shared energy storage system at the time t is represented;
representing an upper power limit for purchasing/selling power to the shared energy storage system;
due to the capacity limitations of the battery and the DC/DC converter, there is an upper limit constraint on the charging and discharging power value of the battery inside the shared energy storage system, and at the same time, there is a lower limit constraint on the power value in order to prevent unnecessary battery loss, and in addition, at each moment, the charging and discharging behaviors of the battery cannot occur simultaneously, as shown in equations (10) to (12):
in the formula (I), the compound is shown in the specification,
a variable of 0 to 1, representing the charge/discharge state of the battery at time t;
representing the charge/discharge power of the battery at time t,
represents the upper/lower power limit for battery charging/discharging;
in order to reduce the loss of the battery and further ensure the service life of the battery, the charge-discharge cycle power constraint of the battery is required to be added:
in the formula (I), the compound is shown in the specification,
represents the maximum charge-discharge cycle power of the battery;
in addition, in order to ensure the sustainable development of the scheduling strategy, the energy of the battery is required to be equal at the beginning and the end of each scheduling period, as formulas (14) to (16):
in the formula (I), the compound is shown in the specification,
representing the energy of the battery inside the shared energy storage system at time t,
represents a minimum/maximum value of battery energy; sigmaESSIndicating the self-discharge rate of the battery.
Because the bidirectional converter inside the shared energy storage system has certain power loss, the efficiency constraint of each device needs to be added:
in the formula etaESS,DC,ACRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from DC to ACESS,AC,DCRepresenting the efficiency, η, of a DC/AC converter converting electrical energy from AC to DCESS,disRepresenting the efficiency, η, of the DC/DC converter when the battery is dischargedESS,chRepresents the efficiency of the DC/DC converter when the battery is charged;
103, an operation model of power interaction of the micro-grid and the active power distribution network is as follows:
the electricity purchasing cost of each micro-grid from the active power distribution network is as follows:
in the formula (I), the compound is shown in the specification,
representing the electricity purchase cost of the microgrid i from the active power distribution network;
the electricity purchasing/selling price of the micro-grid i to the active power distribution network at the time t is represented;
the power of electricity purchased/sold from the microgrid i to the active power distribution network at the moment t is represented;
due to the capacity limitation of the connecting line and the transformer, the interactive power value of each microgrid and the active power distribution network is restricted by upper and lower limits, and meanwhile, the electricity purchasing/selling behaviors of each microgrid and the active power distribution network cannot occur simultaneously at each moment, as shown in formulas (22) to (24):
in the formula (I), the compound is shown in the specification,
the variable is 0-1, and the electricity purchasing/selling state of the microgrid i to the active power distribution network at the moment t is represented;
represents the upper limit of power purchased/sold to the active distribution grid.
4. The method of claim 2, wherein the method comprises: the process for establishing the day-ahead economic optimization scheduling model of the microgrid group with the shared energy storage system in the step 2 is as follows:
step 201, establishing an optimization model objective function:
the optimized objective function is to minimize the total operation cost of the microgrid group, wherein the operation and maintenance cost of the wind turbine and the photovoltaic, the electricity purchasing cost from the active power distribution network, and the electricity purchasing cost from the shared energy storage system are as follows:
in the formula, Cost represents the total operation Cost of the microgrid group; ciRepresenting the operating cost of the microgrid i;
respectively representing the new energy power generation operation maintenance cost of the microgrid i, the electricity purchasing cost from an active power distribution network and the electricity purchasing cost from a shared energy storage system, wherein the calculation methods are respectively shown as formulas (1), (21), (2) to (5);
step 202, establishing an optimization model constraint condition:
1) microgrid electric power balance constraint:
electric power balance must be satisfied inside each microgrid:
2) and (3) sharing electric power balance constraint of the direct current bus of the energy storage system:
the electric power balance relation of the direct current bus of the shared energy storage system satisfies an equation (6);
3) purchasing upper and lower limits of power selling power to the active power distribution network:
the restriction of purchasing and selling the power of the active power distribution network satisfies the formulas (22) - (24);
4) and (3) purchasing and selling power upper and lower limits of the energy storage system to be restricted:
the upper and lower limits of the power purchasing and selling of the shared energy storage system are constrained to satisfy the formulas (7) - (9);
5) the transaction of the shared energy storage system and the active power distribution network through the microgrid is prevented:
for economic and safety reasons, the microgrid is not allowed to sell electric energy purchased from the active power distribution network to the shared energy storage system or to sell electric energy purchased from the shared energy storage system to the active power distribution network at the same time:
6) and (3) battery charging and discharging power constraint of the shared energy storage system:
the battery charge and discharge power constraint of the shared energy storage system satisfies the formulas (10) - (12);
7) and (3) battery charge-discharge cycle power constraint of the shared energy storage system:
the battery charge-discharge cycle power constraint of the shared energy storage system satisfies the formula (13);
8) and (3) battery energy constraint of the shared energy storage system:
the shared energy storage system battery energy constraint satisfies equations (14) - (16);
9) energy conversion efficiency constraint of the shared energy storage system:
the shared energy storage system energy conversion efficiency constraint satisfies equations (17) - (20).
5. The method of claim 2, wherein the method comprises: and 3, solving the day-ahead economic Optimization scheduling model, wherein decision variables comprise the state and power of electricity purchased from each microgrid to the active power distribution network, the state and power of electricity purchased from each microgrid to the shared energy storage system, the charge-discharge state and power of a battery of the shared energy storage system and the energy of the battery of the shared energy storage system, and after acquiring the running cost coefficient and the running limit value of each device in the microgrid group, solving the day-ahead economic Optimization scheduling model by using IBM ILOG CPLEX Optimization Studio in combination with MATLAB to determine a day-ahead scheduling scheme of the microgrid group system.
6. The method of claim 2, wherein the method comprises: the scheduling period is 24 hours, i.e., T-24.
7. The method of claim 2, wherein the method comprises: the scheduling time resolution is 1 hour, i.e., Δ t ═ 1.
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| CN117767375A (en) * | 2024-02-22 | 2024-03-26 | 山东理工大学 | shared energy storage fairness allocation strategy based on risk constraint asymmetric cooperative game |
| CN117767375B (en) * | 2024-02-22 | 2024-05-14 | 山东理工大学 | Shared energy storage fairness allocation strategy based on risk constraint asymmetric cooperative game |
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