CN113870030A - Multi-microgrid energy transaction mechanism design method based on improved Nash bargaining method - Google Patents
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Abstract
The invention discloses a multi-microgrid energy transaction mechanism design method based on an improved Nash bargaining method, which comprises the following steps of: step I: establishing a multi-microgrid operation frame and a multi-microgrid market transaction model; step II: establishing a microgrid mathematical model according to the multi-microgrid operation framework and the multi-microgrid market transaction model; step III: and distributing the operation income of each microgrid by improving a Nash bargaining method according to the microgrid mathematical model. The method takes the operation cost of each microgrid under the non-cooperative game as a negotiation and crack point, establishes a multi-microgrid cooperative operation model, distributes the benefits of each microgrid by using a Nash bargaining theory, and provides a model solving process. The results of the example simulation show that the method can reflect the competition degree of the transaction between the micro-grids, effectively reduce the operating cost of each micro-grid, and reduce the influence on the main grid, and compared with the traditional Nash bargaining and Shapley value distribution scheme, the method can encourage each micro-grid to participate in cooperation.
Description
Technical Field
The invention belongs to the technical field of electric power market transaction optimization, and relates to a multi-microgrid energy transaction mechanism design method based on an improved Nash bargaining method.
Background
With the increasing exhaustion of fossil energy, the large-scale development of renewable energy, and the gradual deterioration of natural environment, the grid-connected microgrid system has become one of the important research directions in the field of distributed energy. The microgrid technology can effectively solve the problem of large-scale distributed power grid connection, reduces impact on power grid operation, and gradually becomes one of the future energy key technologies. However, the traditional independent microgrid has limited regulation capability and cannot further absorb renewable energy. The multi-microgrid technology can realize energy complementary utilization among the microgrids, and has remarkable advantages in the aspects of improving the consumption rate of renewable energy, reducing the operation cost of a system, reducing power interaction to a main network, adding the standby capacity of the system and the like. Due to the effects of photovoltaic devices, energy storage equipment and flexible loads in the microgrid, the microgrid has source-load duality and can participate in energy trading in the power market. However, the problems of competitive games, transaction settlement and the like can be faced when a plurality of micro-grids participate in electric power market transactions, and how to construct a set of scientific and reasonable multi-micro-grid energy transaction mechanism becomes a hotspot of a multi-micro-grid energy market.
Under the framework of a game theory, a research method for energy transaction among micro-grids can be mainly divided into a cooperative game and a non-cooperative game. In the cooperative game, participants generate 'cooperative surplus' by signing a mandatory contract, and the mode emphasizes on improving the overall profit of the alliance. The specific technology is as follows: because the types, parameters and output of equipment such as a renewable power source (a fan, a photovoltaic and the like), a generator set, a heat pump and the like in each micro-grid are different, adjacent micro-grids are interconnected through a power connecting line, mutual power transmission between the adjacent micro-grids can be realized, renewable energy sources which cannot be consumed when each micro-grid operates independently are further consumed, and the phenomena of ' wind abandonment ', light abandonment ' and the like in a large quantity are effectively avoided. The technology is essentially centralized optimization management, and the difficulty of the technology lies in the return allocation after cooperation. The benefit distribution mechanism is vital to optimizing and managing the energy of the microgrid, most of technical researches on multi-microgrid collaborative operation at present utilize Shapley values, Nash bargaining and kernel methods to distribute the benefits of members participating in cooperation, but due to the irrational design of the distribution mechanism, the problems of low positivity of the microgrid participating in cooperation, a power market trading mechanism, low renewable energy consumption rate, poor stability of large grid peak-valley difference increase and the like are caused.
Disclosure of Invention
The invention aims to comprehensively consider factors such as an energy storage device, renewable energy, load shedding, internal transaction and the like aiming at a competition phenomenon in a transaction process between micro-grids, and aims to provide a multi-micro-grid energy transaction mechanism design method based on an improved Nash bargaining method, which can effectively improve the enthusiasm of multi-micro-grid participating in cooperative operation, provide an effective reference scheme for the energy transaction problem of the multi-micro-grid, and overcome the problems of low renewable energy consumption rate and poor stability of large grid peak-valley difference increase in the prior art.
In order to achieve the purpose, the technical scheme of the invention is as follows:
the multi-microgrid energy transaction mechanism design method based on the improved Nash bargaining method comprises the following steps:
step I: establishing a multi-microgrid operation frame and a multi-microgrid market transaction model;
step II: establishing a microgrid mathematical model according to the multi-microgrid operation framework and the multi-microgrid market transaction model;
step III: and distributing the operation income of each microgrid by improving a Nash bargaining method according to the microgrid mathematical model.
A further improvement of the invention is that the multi-microgrid operating framework comprises: the energy trading market comprises a power grid, a micro-grid group trading center and a micro-grid group; the micro-grid and the main grid are in power interaction, and also participate in energy transaction between the micro-grids.
The invention has the further improvement that when the net power in the microgrid is more than zero, electricity needs to be purchased from the main grid or other microgrids, and the microgrid at the moment is an electricity purchasing microgrid; when the net power in the microgrid is less than zero, electricity needs to be sold to the main network or other microgrids, and the microgrid at the moment is an electricity selling microgrid; when the net power in the microgrid is equal to zero, the microgrid does not need to participate in energy transaction, and the microgrid is a balanced microgrid.
The invention has the further improvement that the duality of microgrid transaction is as follows: respectively setting the number of electricity purchasing micro-grids, electricity selling micro-grids and balancing micro-grids as nb、nsAnd neWhen the number n of the electricity-purchasing micro-gridsbOr the number n of electricity-selling micro-gridssWhen the number is equal to zero, all the micro-grids in the market are traded with the main grid; when the number n of the electricity-purchasing micro-gridsbWhen the number is equal to 1, one electricity purchasing micro-grid exists in the market, and competition exists at the electricity selling micro-grid side in the transaction process among the micro-grids; when the number n of the electricity-selling micro-gridssWhen the number is equal to 1, a power selling microgrid exists in the market, and the power purchasing microgrid side has competition in the transaction process among the microgrids; when the number n of the electricity-purchasing micro-gridsbThe number n of the electricity selling micro-gridssWhen the number of the micro grids is larger than 1, competition exists at the micro grid side for selling electricity and purchasing electricity in the transaction process among the micro grids.
The invention has the further improvement that the trading process among the multiple micro-grids is analyzed according to the duality of the micro-grid trading, and a multi-micro-grid market trading model is established:
setting a day to be divided into T periods, assuming that the time-of-use electricity price is adopted by the power grid, and the electricity selling price of the power grid side is higher than the electricity purchasing price, considering the rationality of electricity price setting among the micro-networks, the electricity purchasing and selling prices between the power grid side and the micro-networks in the T-th period in the day are satisfied:
in the formula (I), the compound is shown in the specification,
respectively the electricity purchase and sale prices at the power grid side,
and
the price of electricity purchased and sold among the micro-grids is respectively;
if the total number of the micro-grids is n, the price for buying and selling electricity among the micro-grids in the t-th time period in one day is further represented as follows:
in the formula (I), the compound is shown in the specification,
and
respectively obtaining the electricity purchasing quantity and the electricity selling quantity of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day;
and
for purchasing electricity between micro-networksThe value coefficient of the order of the first and second,
and
the price coefficient of the electricity sold among the micro-networks;
a multi-microgrid market trading model is introduced by combining formulas (1) to (3):
the invention is further improved in that the microgrid mathematical model is established through the following processes:
the microgrid is assumed to be composed of a load, renewable energy sources, energy storage equipment and an energy transaction end; modeling is carried out aiming at the load, the fan, the energy storage equipment, the load shedding, the electric energy transaction and the income of the microgrid, so that a microgrid mathematical model is established;
establishing a fan model: respectively expressing the wind power subsidy and the wind abandoning cost of the microgrid i in the t-th time period in one day as follows:
in the formula, gammasubAnd gammawtThe cost of wind abandonment is unit;
and
respectively representing the output and grid-connected power of the micro-grid fan i in the tth time period in one day, wherein delta t is a research time period;
establishing an energy storage model: assuming that the energy storage devices of all the micro-grids are storage batteries; the use cost of the storage battery of the microgrid i in the t-th time period in one day is set as follows:
in the formula (I), the compound is shown in the specification,
and
respectively representing the charging and discharging power of the storage battery of the microgrid i in the tth time period in one day; alpha is alphaesIs a variable;
the capacity of the microgrid i storage battery in the t +1 th time period in a day is set as follows:
in the formula etacAnd ηdRespectively representing the charging and discharging efficiency of a storage battery in the microgrid;
in order to maintain the service life of the battery, the following constraints are set:
in the formula (I), the compound is shown in the specification,
is the upper limit of the capacity of the storage battery of the microgrid i,
the lower limit of the capacity of the storage battery of the microgrid i,
upper limit of charging and discharging for i storage battery of microgrid and
lower limit of charging and discharging for i storage battery of microgrid
Establishing a load shedding model: assuming that the microgrid has a certain load shedding capability, the load shedding cost and the corresponding constraint of the microgrid i in the t-th time period are set as follows:
in the formula, gammacutAnd
upper limit of unit load shedding cost and allowable load shedding
Establishing an interaction model with a main network: if the interaction power of the microgrid and the main network in the t-th time period is set as
The interaction cost and corresponding constraint of the microgrid i and the main network power in the tth period are as follows:
in the formula (I), the compound is shown in the specification,
an interaction upper limit of the micro-grid i and the main grid power is set;
establishing a power interaction model between micro-grids:
assuming that the purchasing and selling mode of each microgrid in each period of a day is determined by net power, and when the net power in a certain period of the day is greater than/less than/equal to 0, the microgrid in the period is considered as a power purchasing/power selling/balance microgrid; setting the transaction cost and corresponding constraint of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day as follows:
in the formula (I), the compound is shown in the specification,
and
the micro-grid i and the micro-grid participating in market transaction respectively have electricity purchasing and selling upper limits.
The invention is further improved in that the specific process of the step III is as follows:
when each microgrid independently participates in market competition, the objective function is the maximum daily operation yield of each microgrid, and the objective function of the ith microgrid is set as follows:
the constraint conditions of the ith microgrid comprise power balance and market transaction balance in each microgrid:
when all the piconets participate in cooperation, the objective function is the lowest sum of the operating benefits of all the piconets, and is specifically expressed as:
calculating to obtain optimized variables in all the micro-grids through a formula (23), and further distributing the benefits of each micro-grid;
the further improvement of the invention is that if the profit of each microgrid is distributed by adopting a Shapley value method, the operation profit of the ith microgrid in one day is expressed as:
in the formula, SiThe method comprises the steps of representing a set consisting of all subsets comprising the microgrid i, | s | represents the number of elements in the set s, v(s) represents the benefit generated by the set s, and v (s \ i }) represents the set benefit after the microgrid i is removed.
The further improvement of the invention is that the method for allocating the negotiation bursting points by taking the income of each microgrid independently participating in market trading is as follows:
in the formula (I), the compound is shown in the specification,
and CiAnd respectively representing the income of the ith microgrid independently participating in market trading in one period and the operation income after bargaining.
The further improvement of the present invention is that equation (25) is decomposed into two convex sub-problems, which are solved using an IPOPT solver, wherein the two sub-problems are in turn:
in the formula (I), the compound is shown in the specification,
operating revenue of the ith microgrid after optimization for equation (26); ziAnd (4) bargained revenue transfer for the ith microgrid.
Compared with the prior art, the invention has the following beneficial effects: the multi-microgrid dynamic electricity price transaction mechanism design method can reflect the competition degree of transactions among the microgrids, namely the electricity price for buying and selling is in direct proportion to the electricity quantity for buying and selling among the microgrids; compared with the traditional method that each micro-grid independently interacts with the main grid, the multi-micro-grid energy transaction model established by the invention can effectively reduce the operation cost of each micro-grid and reduce the influence on the main grid; compared with the traditional scheme of Nash bargaining and Shapley value distribution, the method can effectively encourage each microgrid to participate in cooperative operation for a long time, promote power trading between adjacent microgrids, and further maintain the stability of each trading subject participating in power trading in the power market. Meanwhile, the running cost of all micro-grids can be effectively reduced, the consumption rate of renewable energy sources is improved, the power interaction influence on the large power grid is reduced, the running reliability of the large power grid is improved, and a set of scientific and feasible reference scheme is provided for technical personnel of multi-micro-grid energy source transaction.
Furthermore, the invention is a set of scientific and reasonable energy transaction mechanism among multiple micro networks. The multi-microgrid market trading model is established on the basis of dynamic electricity prices by establishing a multi-microgrid operation framework, and different from the traditional Nash bargaining method, the multi-microgrid cooperative operation model is established by taking the operation cost of each microgrid under a non-cooperative game as a negotiation and cracking point, the benefits of each microgrid are distributed by using an improved Nash bargaining method, and a model solving process is given to realize the benefit distribution of each microgrid. Simulation results show that: the invention can reflect the competition degree of transactions among the micro-grids, effectively reduce the operation cost of each micro-grid and reduce the influence on the main grid.
Drawings
Fig. 1 is a multi-microgrid energy transaction framework.
Fig. 2 is a microgrid internal energy flow diagram.
Fig. 3 is a prediction curve of wind power and load of each microgrid in one day.
Fig. 4 is a net load curve of each microgrid during a day.
Fig. 5 is an optimized operation curve of the devices in each microgrid in the next day.
Fig. 6 is a result of optimizing the price of electricity purchased and sold in the microgrid group according to the present invention.
Detailed Description
The invention is further described in detail below with reference to the figures and specific examples.
Aiming at the competition phenomenon in the transaction process between micro-grids, factors such as an energy storage device, renewable energy, load shedding and internal transaction are comprehensively considered, a scientific and reasonable multi-micro-grid energy transaction mechanism based on an improved Nash bargaining method is provided, a multi-micro-grid operation framework is established, a multi-micro-grid market transaction model is established based on dynamic electricity price, the enthusiasm of multi-micro-grid participation in cooperative operation can be effectively improved, and an effective reference scheme is provided for the energy transaction problem of the multi-micro-grid.
Different from the traditional Nash bargaining method, the method takes the running cost of each microgrid under the non-cooperative game as a negotiation breaking point, establishes a multi-microgrid cooperative running model, distributes the benefits of each microgrid by using the improved Nash bargaining method, and provides a model solving flow.
The invention mainly comprises the following steps:
step I: establishing a multi-microgrid operation frame and a multi-microgrid market transaction model;
step II: establishing a microgrid mathematical model under the background of a market transaction mechanism according to the multi-microgrid operation framework;
step III: aiming at the problem of profit allocation of cooperative operation of each microgrid, designing and improving a Nash bargaining method to obtain the profit of each microgrid for allocation;
step IV: carrying out example simulation analysis;
specifically, the present invention includes the following processes:
step I: establishing a multi-microgrid operation frame and a multi-microgrid market transaction model;
(1) the multi-microgrid energy transaction framework comprises:
referring to fig. 1, the multi-microgrid energy transaction framework provided by the invention comprises: the energy trading market comprises a power grid, a micro-grid group trading center and a micro-grid group. The micro-grid can not only perform power interaction with the main grid, but also participate in energy transaction between the micro-grids.
(2) Analyzing the duality of the microgrid transaction:
because the microgrid contains renewable energy sources, the microgrid has trade duality: when the net power in the microgrid is more than zero, electricity needs to be purchased from the main grid or other microgrids, and the microgrid at the moment is an electricity purchasing microgrid; when the net power in the microgrid is less than zero, electricity needs to be sold to the main network or other microgrids, and the microgrid at the moment is an electricity selling microgrid; when the net power in the microgrid is equal to zero, the microgrid does not need to participate in energy transaction, and the microgrid is a balanced microgrid.
(3) Designing a transaction process among multiple micro networks:
because some microgrids have weak competitiveness during competition games among the microgrids, the microgrids can cooperate with other microgrids before participating in transactions, and a transaction strategy and income distribution are determined by signing a contract. And after each microgrid determines whether to cooperate with other microgrids, each microgrid or microgrid alliance transmits the electricity purchasing and selling quantity in one day to the trading center, the trading center performs buying and selling matching, and the clear amount of the trades is disclosed after the matching is completed.
(4) Transaction competition analysis:
respectively setting the number of electricity purchasing micro-grids, electricity selling micro-grids and balancing micro-grids as nb、nsAnd neAnalyzing the market transaction condition: when the number n of the electricity-purchasing micro-gridsbOr the number n of electricity-selling micro-gridssWhen the number is equal to zero, all the micro-grids in the market are traded with the main grid; when the number n of the electricity-purchasing micro-gridsbWhen the number is equal to 1, only one electricity purchasing micro-grid exists in the market, and only the electricity selling micro-grid side has competition in the transaction process among the micro-grids; when the number n of the electricity-selling micro-gridssWhen the number is equal to 1, only one electricity-selling micro-grid exists in the market, and only the electricity-purchasing micro-grid side has competition in the transaction process among the micro-grids; when the number n of the electricity-purchasing micro-gridsbThe number n of the electricity selling micro-gridssWhen the number of the micro grids is larger than 1, competition exists at the micro grid side for selling electricity and purchasing electricity in the transaction process among the micro grids.
(5) Analyzing the transaction process among multiple micro-grids according to the duality of micro-grid transaction, and establishing a multi-micro-grid market transaction model:
the day is divided into T time periods, and the time-of-use electricity price is assumed to be adopted by the power grid, and the electricity selling price on the power grid side is higher than the electricity purchasing price. The micro-grid group and the main grid are subjected to power interaction and then are price arbitrage, and the micro-grid group can increase income by setting the electricity purchasing and selling prices among the micro-grids. Considering the rationality of the electricity price setting between the micro-networks, the electricity price for buying and selling between the power grid side and the micro-networks in the t-th time period in a day should meet the following requirements:
in the formula (I), the compound is shown in the specification,
respectively the electricity purchase and sale prices at the power grid side,
and
the prices of electricity purchased and sold among the micro-grids are respectively.
In order to reflect the game competition relationship among the micro-networks, the invention provides that the transaction electricity price among the micro-networks adopts a dynamic electricity price mechanism. According to the characteristics of buyers and sellers in market transactions: when the total electricity purchasing amount in the trading market is large, the electricity purchasing price among the micro-networks is increased; when the total electricity selling amount in the trading market is larger, the electricity selling price between the micro-networks is reduced. If the total number of the micro-grids is n, the price of electricity purchased and sold among the micro-grids in the t-th time period in a day can be further expressed as:
in the formula (I), the compound is shown in the specification,
and
respectively obtaining the electricity purchasing quantity and the electricity selling quantity of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day;
and
the price coefficients of the purchased and sold electricity among the micro-grids are respectively.
The multi-microgrid market trading model can be derived by combining the formulas (1) to (3):
step II: establishing micro-grid mathematical model
Referring to fig. 2, assume that the microgrid is composed of loads, renewable energy sources, energy storage devices, and energy trading terminals. And modeling is carried out aiming at the load, the fan, the energy storage equipment, the load shedding, the electric energy transaction and the income of the micro-grid, and a multi-micro-grid market transaction mechanism is further constructed.
(1) Establishing a fan model:
the wind turbine is used for generating power by relying on wind energy in the nature, but the utilization rate of renewable energy sources of the micro-grid is reduced due to large-scale wind abandoning. Respectively expressing the wind power subsidy and the wind abandoning cost of the microgrid i in the t-th time period in one day as follows:
in the formula, gammasubAnd gammawtThe cost of wind abandonment is unit;
and
the output and the grid-connected power of the micro-grid i fan in the t-th time period in one day are respectively represented, and delta t is a research time period.
(2) Establishing an energy storage model:
the energy storage devices can realize the space-time transfer of electric energy, and the energy storage devices of all the micro-grids are assumed to be storage batteries. The use cost of the storage battery of the microgrid i in the t-th time period in one day is set as follows:
in the formula (I), the compound is shown in the specification,
and
respectively representing the charging and discharging power of the storage battery of the microgrid i in the tth time period in one day; alpha is alphaesIs an integer variable of 0-1, and takes 1 when charging and 0 when discharging.
The capacity of the microgrid i storage battery in the t +1 th time period in a day is set as follows:
in the formula etacAnd ηdAnd respectively shows the charging and discharging efficiency of the storage battery in the microgrid.
In order to maintain the service life of the battery, the following constraints are set:
in the formula (I), the compound is shown in the specification,
is the upper limit of the capacity of the storage battery of the microgrid i,
the lower limit of the capacity of the storage battery of the microgrid i,
upper limit of charging and discharging for i storage battery of microgrid and
and the charge-discharge lower limit of the storage battery of the microgrid i is set.
(3) Establishing a load shedding model:
because no generator set is arranged in each microgrid, in order to maintain the internal power balance of the microgrid, the microgrid is assumed to have certain load shedding capacity. And setting the load shedding cost and the corresponding constraint of the microgrid i in the t-th time period as follows:
in the formula, gammacutAnd
the unit load shedding cost and the upper limit of the allowable load shedding are respectively.
(4) And (3) establishing an interaction model with the main network:
if the interaction power of the microgrid and the main network in the t-th time period is set as
The interaction cost and corresponding constraint of the microgrid i and the main network power in the tth period are as follows:
in the formula (I), the compound is shown in the specification,
and forming an interaction upper limit for the micro-grid i and the main grid power.
(5) Establishing a power interaction model between the micro networks:
to prevent price arbitrage for the piconets, it is assumed that the purchase and sale mode of each piconet during each time of day is determined by net power. And when the net power of a certain time period in one day is more than or less than or equal to 0, the microgrid in the time period is considered as the electricity purchasing/electricity selling/balance microgrid. Setting the transaction cost and corresponding constraint of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day as follows:
in the formula (I), the compound is shown in the specification,
and
the micro-grid i and the micro-grid participating in market transaction respectively have electricity purchasing and selling upper limits.
Step III: design and improvement of Nash bargaining method
The traditional Nash bargaining method takes the income of each microgrid under independent operation as a negotiation collapse point, and further settles the income of each microgrid. However, this approach has limitations: (1) the situation that each microgrid participates in market trading is not considered; (2) the revenue from some piconets participating in market competition alone may be higher than the revenue from allocations under traditional nash bargaining methods. In view of the above two problems, the improved nash bargaining method proposed by the present invention is as follows:
(1) determining negotiation breakout points:
when each microgrid independently participates in market competition, the objective function is the maximum daily operation yield of each microgrid, and the objective function of the ith microgrid is set as follows:
the constraints of the ith piconet are based on equations (1) - (3), (9) - (11), (13), (15), and (17) - (19), and the power balance and market trade balance in each piconet should be considered:
based on the objective function and the constraint condition, the transaction competition problem among the multiple micro-networks belongs to the non-cooperative game category, and the game problem is specifically described as follows.
The game participants are traders participating in the microgrid trading market and are denoted by N ═ 1,2, …, N.
The strategy of each participant comprises the purchase and sale electricity quantity, the energy storage device output and the load shedding quantity of other participants and the main network, and the strategy of the ith participant is expressed as siAnd the corresponding constraint conditions are met, and each trader maximizes the income per se by adjusting the strategy.
The ith participant is selecting a strategy siTime gain CiSee formula (20).
The specific solving steps of the game problem are as follows:
1) and inputting data and information of the multi-microgrid system, and acquiring a microgrid user load and renewable energy source prediction curve.
2) Determining a transaction mode according to the net load of each microgrid: when the net load of a certain period is larger than zero, the trader is considered to sell electricity in the period; when the net load of a certain period is less than zero, the trader is considered to purchase electricity in the period.
3) And setting the initial value of the purchase and sale electricity quantity among the micro-networks.
4) Aiming at the microgrid i, the strategy under the maximum value of the formula (20) is solved by using an interior point method
Preserving maximum profit value
And updates the current policy.
5) On the basis of updating the strategy of the trader i, the optimal strategy and the corresponding income of all traders are sequentially solved, similar to the step 4). If the strategies of all traders are not changed any more, outputting Nash equilibrium solutions of the strategies of all traders; otherwise, returning to the step 4).
(2) Shapley value method based on cooperative game:
when all the micro-grids participate in cooperation, the cooperative game theory can be applied for analysis, and the target function is the lowest sum of the operating benefits of all the micro-grids and is specifically expressed as follows:
the equation (23) may calculate the optimized variables in all the piconets, and further needs to distribute the revenue of each piconet. If the sharey value method is adopted for distribution, the operating yield of the ith microgrid in a day can be expressed as:
in the formula, SiThe method comprises the steps of representing a set consisting of all subsets comprising the microgrid i, | s | represents the number of elements in the set s, v(s) represents the benefit generated by the set s, and v (s \ i }) represents the set benefit after the microgrid i is removed.
(3) An improved Nash bargaining method based on cooperative game comprises the following steps:
when the total optimization operation yield of the multiple micro-grids is maximum, in order to achieve the optimal overall objective function, the phenomenon that individual micro-grids sacrifice the benefits of the micro-grids may exist. Therefore, a scientific and reasonable revenue distribution mechanism needs to be further discussed to maintain the enthusiasm of each microgrid participating in cooperative operation. The invention provides an improved Nash bargaining method for distributing the operation income of each microgrid, the method can simultaneously meet four properties of symmetry, pareto optimality, independent and irrelevant selection and linear transformation invariance, the income of each microgrid independently participating in market trading is taken as a negotiation and crack point, and the established model is specifically expressed as follows:
in the formula (I), the compound is shown in the specification,
and CiAnd respectively representing the income of the ith microgrid independently participating in market trading in one period and the operation income after bargaining.
Considering that equation (25) is a non-convex nonlinear problem, decomposing the non-convex nonlinear problem into two convex sub-problems, and solving the convex sub-problems by using an IPOPT solver, wherein the decomposed sub-problems sequentially comprise:
in the formula (I), the compound is shown in the specification,
operating revenue of the ith microgrid after optimization for equation (26); ziAnd (4) bargained revenue transfer for the ith microgrid.
Step IV: performing example simulation analysis
The simulation is carried out by taking the scene of 4 micro-grids as a calculation example, each micro-grid is provided with a fan and energy storage equipment, each micro-grid is connected with a main grid, and power mutual transmission among the micro-grids can be realized through a connecting line. The power interaction limits among the micro grids and between the micro grids and the main grid are respectively 100kW and 150 kW; the upper limit of the load cutting is 150kW, and the cost of the load cutting is 5 yuan/kW; the rated capacity of all energy storage equipment is 300kWh, the initial capacity is 60kWh, the charge and discharge power limit is 60kW, the upper and lower allowable capacity limits are 270kWh and 60kWh respectively, and the unit charge and discharge cost is 2 yuan/kW. A 24-hour day period was used as the study period, and the electricity rates of the grid during one day are shown in table 1. The fan output, load prediction curve and net load curve of each microgrid during one day are respectively shown in fig. 3 and fig. 4.
TABLE 1 time-of-use electricity price of electric network
In order to verify the validity of the model of the present invention, the following four modes were set for comparative analysis.
Mode 1: electric energy transaction is not carried out inside all micro grids;
mode 2: each micro-grid independently carries out electric energy transaction without considering the cooperation phenomenon among the micro-grids;
mode 3: all the micro-grids perform cooperative game and are distributed by adopting a Shapley value method;
mode 4: the invention provides an improved Nash bargaining model based on cooperative game.
By performing simulation on the MATLAB platform, the daily operation optimization gains of each microgrid in the modes 1-4 are shown in Table 2:
table 2 optimized gains for daily operation of each microgrid in modes 1 to 4
From table 2 it can be found that: the internal trading electricity price model constructed by the invention can effectively improve the operation benefits of each microgrid. This is because the buyer microgrid and the seller microgrid can gain profit from each other by performing transactions through internal electricity prices in mode 2, compared to performing transactions directly with the power grid in mode 1. In the mode 3, the cooperative cooperation of the micro-grids improves the benefits of all the micro-grids, but not all the micro-grids are necessarily involved in cooperation, compared with independent participation in market competition (mode 2), the benefits of the MG 2-MG 4 are respectively improved by 13.7%, 7.95% and 12.1%, and the benefit of the MG1 is reduced by 26.86%, so that the MG1 is more prone to independently participate in the market competition, and the initiative of cooperation is broken. The improved nash bargaining distribution method (mode 4) provided by the invention enables the income of all MGs to be improved by 126.69 yuan compared with the situation that each microgrid independently participates in market trading, which is consistent with the mathematical derivation of the nash bargaining theory, and further verifies the effectiveness of the method. For each microgrid, the gains of the MG 1-MG 4 are respectively improved by 3.87%, 2.68%, 2.54% and 4.27%, which is beneficial to maintaining the microgrid group to cooperate for a long time.
The results of the optimization of the interaction power between the micro-networks, the interaction power with the power grid, the output of the energy storage device and the load shedding in the day in the mode 4 are shown in fig. 5, and the results of the optimization of the internal purchase and sale electricity price in the day in the mode 4 are shown in fig. 6.
Aiming at the multi-microgrid energy trading problem under the power market environment, a multi-microgrid trading model based on an improved Nash bargaining method is provided, and the method has the following advantages:
(1) each micro-grid can effectively improve the operation income of each micro-grid through internal power transaction, promote many micro-grid systems to consume system net electric power on the spot, reduce the power interaction with the major network.
(2) The dynamic electricity price purchasing and selling model can reflect the competition degree of each microgrid participating in the market, and is more suitable for the scene of the actual power market.
(3) The improved Nash bargaining model can well balance the income of each microgrid by comparing the income of each microgrid under two situations of non-cooperative game and cooperative game, and maintains the enthusiasm of long-term cooperation of microgrid groups.
Claims (10)
1. The multi-microgrid energy transaction mechanism design method based on the improved Nash bargaining method is characterized by comprising the following steps of:
step I: establishing a multi-microgrid operation frame and a multi-microgrid market transaction model;
step II: establishing a microgrid mathematical model according to the multi-microgrid operation framework and the multi-microgrid market transaction model;
step III: and distributing the operation income of each microgrid by improving a Nash bargaining method according to the microgrid mathematical model.
2. The method for designing a multi-microgrid energy transaction mechanism based on an improved Nash bargaining method according to claim 1, wherein the multi-microgrid operation framework comprises: the energy trading market comprises a power grid, a micro-grid group trading center and a micro-grid group; the micro-grid and the main grid are in power interaction, and also participate in energy transaction between the micro-grids.
3. The method as claimed in claim 2, wherein when the net power in the microgrid is greater than zero, electricity needs to be purchased from the main grid or other microgrids, and the microgrid is an electricity purchasing microgrid; when the net power in the microgrid is less than zero, electricity needs to be sold to the main network or other microgrids, and the microgrid at the moment is an electricity selling microgrid; when the net power in the microgrid is equal to zero, the microgrid does not need to participate in energy transaction, and the microgrid is a balanced microgrid.
4. The method for designing a multi-microgrid energy transaction mechanism based on an improved Nash bargaining method as claimed in claim 1, wherein the duality of microgrid transaction is as follows: respectively setting the number of electricity purchasing micro-grids, electricity selling micro-grids and balancing micro-grids as nb、nsAnd neWhen the number n of the electricity-purchasing micro-gridsbOr the number n of electricity-selling micro-gridssWhen the number is equal to zero, all the micro-grids in the market are traded with the main grid; when the number n of the electricity-purchasing micro-gridsbIs equal to 1In time, a power-purchasing micro-grid is arranged in the market, and competition exists at the power-selling micro-grid side in the inter-micro-grid transaction process; when the number n of the electricity-selling micro-gridssWhen the number is equal to 1, a power selling microgrid exists in the market, and the power purchasing microgrid side has competition in the transaction process among the microgrids; when the number n of the electricity-purchasing micro-gridsbThe number n of the electricity selling micro-gridssWhen the number of the micro grids is larger than 1, competition exists at the micro grid side for selling electricity and purchasing electricity in the transaction process among the micro grids.
5. The method for designing the multi-microgrid energy transaction mechanism based on the improved Nash bargaining method as claimed in claim 4, wherein the transaction process among the multiple microgrids is analyzed according to the duality of microgrid transaction, and a multi-microgrid market transaction model is established:
setting a day to be divided into T periods, assuming that the time-of-use electricity price is adopted by the power grid, and the electricity selling price of the power grid side is higher than the electricity purchasing price, considering the rationality of electricity price setting among the micro-networks, the electricity purchasing and selling prices between the power grid side and the micro-networks in the T-th period in the day are satisfied:
in the formula (I), the compound is shown in the specification,
respectively the electricity purchase and sale prices at the power grid side,
and
the price of electricity purchased and sold among the micro-grids is respectively;
if the total number of the micro-grids is n, the price for buying and selling electricity among the micro-grids in the t-th time period in one day is further represented as follows:
in the formula (I), the compound is shown in the specification,
and
respectively obtaining the electricity purchasing quantity and the electricity selling quantity of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day;
and
for the electricity price coefficient of the purchase between the micro-networks,
and
the price coefficient of the electricity sold among the micro-networks;
a multi-microgrid market trading model is introduced by combining formulas (1) to (3):
6. the method for designing the multi-microgrid energy transaction mechanism based on the improved Nash bargaining method is characterized in that a microgrid mathematical model is established through the following processes:
the microgrid is assumed to be composed of a load, renewable energy sources, energy storage equipment and an energy transaction end; modeling is carried out aiming at the load, the fan, the energy storage equipment, the load shedding, the electric energy transaction and the income of the microgrid, so that a microgrid mathematical model is established;
establishing a fan model: respectively expressing the wind power subsidy and the wind abandoning cost of the microgrid i in the t-th time period in one day as follows:
in the formula, gammasubAnd gammawtThe cost of wind abandonment is unit;
and
respectively representing the output and grid-connected power of the micro-grid fan i in the tth time period in one day, wherein delta t is a research time period;
establishing an energy storage model: assuming that the energy storage devices of all the micro-grids are storage batteries; the use cost of the storage battery of the microgrid i in the t-th time period in one day is set as follows:
in the formula (I), the compound is shown in the specification,
and
respectively representing the charging and discharging power of the storage battery of the microgrid i in the tth time period in one day; alpha is alphaesIs a variable;
the capacity of the microgrid i storage battery in the t +1 th time period in a day is set as follows:
in the formula etacAnd ηdRespectively representing the charging and discharging efficiency of a storage battery in the microgrid;
in order to maintain the service life of the battery, the following constraints are set:
in the formula (I), the compound is shown in the specification,
is the upper limit of the capacity of the storage battery of the microgrid i,
the lower limit of the capacity of the storage battery of the microgrid i,
upper limit of charging and discharging for i storage battery of microgrid and
lower limit of charging and discharging for i storage battery of microgrid
Establishing a load shedding model: assuming that the microgrid has a certain load shedding capability, the load shedding cost and the corresponding constraint of the microgrid i in the t-th time period are set as follows:
in the formula, gammacutAnd
upper limit of unit load shedding cost and allowable load shedding
Establishing an interaction model with a main network: if the interaction power of the microgrid and the main network in the t-th time period is set as
The interaction cost and corresponding constraint of the microgrid i and the main network power in the tth period are as follows:
in the formula (I), the compound is shown in the specification,
an interaction upper limit of the micro-grid i and the main grid power is set;
establishing a power interaction model between micro-grids:
assuming that the purchasing and selling mode of each microgrid in each period of a day is determined by net power, and when the net power in a certain period of the day is greater than/less than/equal to 0, the microgrid in the period is considered as a power purchasing/power selling/balance microgrid; setting the transaction cost and corresponding constraint of the microgrid i and the microgrid participating in market transaction in the t-th time period in one day as follows:
in the formula (I), the compound is shown in the specification,
and
the micro-grid i and the micro-grid participating in market transaction respectively have electricity purchasing and selling upper limits.
7. The method for designing the multi-microgrid energy transaction mechanism based on the improved Nash bargaining method as claimed in claim 6, wherein the specific process of step III is as follows:
when each microgrid independently participates in market competition, the objective function is the maximum daily operation yield of each microgrid, and the objective function of the ith microgrid is set as follows:
the constraint conditions of the ith microgrid comprise power balance and market transaction balance in each microgrid:
when all the piconets participate in cooperation, the objective function is the lowest sum of the operating benefits of all the piconets, and is specifically expressed as:
calculating to obtain optimized variables in all the micro-grids through a formula (23), and further distributing the benefits of each micro-grid;
8. the method as claimed in claim 7, wherein if the operating revenue of each microgrid is distributed by using a sharey value method, the operating revenue of the ith microgrid in a day is expressed as:
in the formula, SiThe method comprises the steps of representing a set consisting of all subsets comprising the microgrid i, | s | represents the number of elements in the set s, v(s) represents the benefit generated by the set s, and v (s \ i }) represents the set benefit after the microgrid i is removed.
9. The method for designing the multi-microgrid energy trading mechanism based on the improved Nash bargaining method as claimed in claim 8, wherein the method for allocating the negotiation breaking points by using the income of independent participation of each microgrid in market trading is as follows:
in the formula (I), the compound is shown in the specification,
and CiAnd respectively representing the income of the ith microgrid independently participating in market trading in one period and the operation income after bargaining.
10. The method for designing the multi-microgrid energy trading mechanism based on the improved Nash bargaining method as claimed in claim 9, wherein the equation (25) is decomposed into two convex subproblems, and the solving is performed by using an IPOPT solver, wherein the two subproblems are sequentially:
in the formula (I), the compound is shown in the specification,
operating revenue of the ith microgrid after optimization for equation (26); ziAnd (4) bargained revenue transfer for the ith microgrid.
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