CN113869927B - Time-sharing pricing method for promoting energy sharing of multiple producers and consumers in community micro-grid - Google Patents

Time-sharing pricing method for promoting energy sharing of multiple producers and consumers in community micro-grid Download PDF

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CN113869927B
CN113869927B CN202110335272.7A CN202110335272A CN113869927B CN 113869927 B CN113869927 B CN 113869927B CN 202110335272 A CN202110335272 A CN 202110335272A CN 113869927 B CN113869927 B CN 113869927B
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CN113869927A (en
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高红均
徐松
刘友波
刘俊勇
王乃永
吴子豪
王若谷
王辰曦
唐露甜
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Sichuan University
State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Shanxi Electric Power Co Ltd
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Shanxi Electric Power Co Ltd
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Abstract

The invention discloses a time-sharing pricing method for promoting energy sharing of prolifics and weapons in a community micro-grid, which relates to the technical field of electricity market at the electricity selling side and comprises the following steps: step 1, analyzing characteristics of sharing transaction markets of multiple-yield consumers in a community micro-grid, and constructing a sharing transaction framework of the multiple-yield consumers in the community micro-grid; step 2, aiming at a sharing transaction framework of the multi-product and the consumer in the community micro-grid, designing a sharing transaction time-of-use electricity price mechanism of the multi-product and the consumer in the community micro-grid; step 3, modeling the internal flexible resources of the producer and the consumer, and constructing a producer and consumer main body market decision model based on a two-stage robust model; and 4, solving a shared transaction time-of-use electricity price mechanism of the multi-producer and the consumer in the community micro-grid through an iteration solving framework embedded with a column and constraint generating algorithm.

Description

Time-sharing pricing method for promoting energy sharing of multiple producers and consumers in community micro-grid
Technical Field
The invention relates to the technical field of electricity market at the electricity selling side, in particular to a time-sharing pricing method for promoting energy sharing of multiple producers and consumers in a community micro-grid.
Background
In recent years, energy policies of various countries in the world encourage end users to install roof photovoltaic power generation systems, and the policies drive a brand new producer and consumer body to appear in a smart grid, so that the generated energy of a large-scale photovoltaic unit can fluctuate, and the uncertainty brought by the generated energy can have great influence on the safe operation of a power distribution system. The energy transaction between adjacent producers and consumers can improve the on-site utilization of the photovoltaic power generation and reduce the negative influence on a power system. At the same time, these producers and consumers with a variety of flexible resources (e.g., controllable loads, energy storage systems) have flexibility in the time of their energy consumption. Therefore, how to effectively and fully utilize these flexible resources in the energy sharing trade market design and promote the energy sharing among producers and consumers is a problem to be solved in the future.
However, the existing designs have the following problems:
1. the method for carrying out detailed analysis modeling on the operation of flexible resources in the main body of the producer and the consumer of different types and effectively sharing and trading energy among the producers and consumers is lacking.
2. The design of a time-sharing pricing mechanism is not considered to encourage producers and consumers to adjust the operation plan of the internal flexible resources, so that the on-site utilization of photovoltaic power generation is promoted.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a time-sharing pricing method for promoting energy sharing of multiple producers and consumers in a community micro-grid.
The aim of the invention is realized by the following technical scheme:
a time-sharing pricing method for promoting energy sharing of multiple producers and consumers in a community micro-grid comprises the following steps of
Step 1, analyzing characteristics of sharing transaction markets of multiple-yield consumers in a community micro-grid, and constructing a sharing transaction framework of the multiple-yield consumers in the community micro-grid;
step 2, aiming at a sharing transaction framework of the multi-product and the consumer in the community micro-grid, designing a sharing transaction time-of-use electricity price mechanism of the multi-product and the consumer in the community micro-grid;
step 3, modeling the internal flexible resources of the producer and the consumer, and constructing a producer and consumer main body market decision model based on a two-stage robust model;
and 4, solving a shared transaction time-of-use electricity price mechanism of the multi-producer and the consumer in the community micro-grid through an iteration solving framework embedded with a column and constraint generating algorithm.
Preferably, in the step 1, characteristics of the sharing transaction market of the multi-product consumers in the community micro-grid are analyzed, and a sharing transaction framework of the multi-product consumers in the community micro-grid is constructed. The producers and the consumers serve as independent benefit bodies, and the producer and the consumer bodies are connected with each other through adjacent feeder lines to form a community micro-grid. Because they have the same objectives (e.g., economy, reliability, and environmental issues, etc.), they can be controlled and managed as a whole. And different producers and consumers may have loads (e.g., office, industrial, commercial, etc.) with different peak electricity usage periods, so that energy sharing between different producers and consumers can maximally utilize renewable energy within the community microgrid.
Because the existing electricity selling side market is not mature enough, the method introduces the community micro-grid energy coordination management main body to uniformly manage the energy sharing among the community micro-grid power generation and consumption agents, and mainly has the effects of organizing the power generation and consumption agents to participate in the community micro-grid internal energy sharing transaction market, collecting the purchase and sales electricity quantity of the power generation and consumption agents in the energy sharing transaction market, and determining and releasing the transaction time-sharing electricity price of the power generation and consumption agents in the energy sharing market.
Preferably, the step 2 designs a shared transaction time-sharing pricing mechanism for multiple producers and consumers in the community micro-network, and the supply and the demand areBasic concept of economics. In the community micro-grid energy sharing market, the total sales power of all sellers with the value of t time period is suppliedThe required value is t time period total purchase amount of all buyers +.>The internal buying and selling prices of all periods in the community micro-grid energy sharing market are determined by all producers and consumers together, so that fairness of sharing transactions among all consumer bodies can be guaranteed. The SDR of each period t of the community micro-grid energy sharing market is defined as:
the total sales electricity quantity and the total purchase electricity quantity of the community micro-grid energy sharing market generator and eliminator main body are respectively.
Considering fluctuation of photovoltaic power generation and load, the supply-demand ratio is different in different time periods, and a community micro-grid sharing market trading price set is defined to reflect the fluctuation according to the sharing trading price inside the community micro-grid in different operation time periods.
Community micro-grid energy coordination managementThe principal is a proxy for all the producer and consumer principal, which is represented by lambda s,buy And lambda (lambda) buy To purchase electric energy from the main body of the consumer and the distribution network operator, respectively, and to use lambda s,sell And lambda (lambda) sell The prices of (a) sell electricity to the consumer main body and the distribution network operator, respectively.
In order to promote the internal load of the producer and the consumer to consume electric energy when the community micro-grid energy is surplus, the relationship between the community micro-grid energy sharing transaction price and the supply-demand ratio should be in an inverse proportion relationship. Therefore, we can use this principle to make electricity prices. Firstly, under the constraint of the internet power price, the sharing transaction time-sharing power price in the community micro-grid is defined as a piecewise function of the supply-demand ratio:
wherein, the price is compensated for lambda (lambda is more than or equal to 0 and less than or equal to lambda) buy -λ sell ) The method is used for compensating the participation of the producers and the consumers in the community micro-grid energy sharing market to obtain more profits. In particular, when the supply-demand ratio is greater than 1, if the offset price λ is zero, the electricity selling price and the electricity purchasing price of the sharing market in the community micro-grid are both equal to the trading electricity price with the power distribution network operator, which cannot guarantee that the producers and consumers voluntarily participate in the community micro-grid energy sharing market.
Preferably, the step 3 analyzes the energy consumption time characteristics of the multi-type flexible resources in the producer and the consumer, and models and analyzes the operation constraint of the producer and the consumer.
Objective function of the producer-consumer body decision model:
the objective function mainly comprises electricity purchasing and selling cost, air conditioning and load-transferable adjustment cost, operation cost of an energy storage system and operation cost of a photovoltaic unit in the community micro-grid energy sharing market, and the detailed calculation formula is as follows.
In the method, in the process of the invention,respectively an air conditioner, a transferable load, an energy storage system and an operation cost coefficient of a photovoltaic system,
the operation constraint of the heating ventilation air conditioner is as follows:
the heating ventilation air conditioning unit can reduce the indoor temperature in summer and raise the indoor temperature in winter, thereby providing more comfortable indoor environment for people, and being an important flexible resource in the body of the producer and the consumer. According to indoor and outdoor temperaturesThe transformation rule mainly considers the relation between the air conditioner power and the temperature, the range of the indoor temperature, and the like. Wherein the method comprises the steps ofAnd->Indoor and outdoor temperatures, η n And R is n Heating capacity and thermal resistance of the heating, ventilation and air conditioning unit respectively, < >>The power of the air conditioning unit is the running power of the heating ventilation air conditioning unit.
The transferable load operation constraint is:
the power consumption of the transferable load can be adjusted in each operation period, but the total power consumption of the whole operation period is required to be kept as a constant, and the power consumption adjustment of each period is required to be kept within an allowable range. Wherein the method comprises the steps ofFor a load transferable predictive value, +.>For the adjusted value, +.>The ratio is adjusted to the maximum.
The operation constraint of the energy storage system is as follows:
the energy storage system can only charge or discharge for a certain period of time, wherein;the charging and discharging state is a charging and discharging state of the energy storage system in a certain time period; the charge and discharge amount per unit time is limited to an allowable range, wherein->Charge/discharge amount per unit operation period, P i ess,max The maximum charge and discharge amount of the energy storage system in unit time is set; the state of charge of the energy storage system is to be kept within a limit, wherein +.>For the charge of a certain period of time of the energy storage system, < ->For the charge and discharge efficiency of the energy storage system,/>is the maximum and minimum charge of the energy storage system.
Output constraint of the photovoltaic unit:
the output value of the photovoltaic unit is smaller than the predicted scene, whereinThe actual output value of the photovoltaic unit.
The electricity purchasing constraint of the main body of the producing and eliminating person:
the transaction electric quantity of the producer and the consumer in the community micro-grid sharing market is kept within the safety constraint range in a certain time period, and the producer and consumer can only select to purchase or sell electricity in the same time period. Wherein the method comprises the steps ofFor the electricity purchasing state of the body of the producing and eliminating person, < ->The maximum transaction capacity of the transaction market is shared with the community micro-grid for each operation period of the consumer body.
The producer-consumer body internal power balance constraint:
in any time period, the electricity purchasing quantity of the producer and the consumer body, the photovoltaic output value, the energy storage and discharge quantity and the load electricity consumption quantity are balanced.
Preferably, in the step 4, the uncertainty of the output of the photovoltaic unit in the generator and the generator is considered, and a two-stage robust optimization decision model of the generator and the generator is constructed to handle the risk that the uncertainty of the output of the photovoltaic unit in the generator and the generator may cause to the participation of the generator and the generator, and the decision model of the generator and the generator is actually a quadratic programming problem, so that the decision model of the generator and the generator can be expressed as the following matrix form for facilitating the subsequent discussion.
s.t.A n x n ≤c n
B n x n ＝0
C n y n ≤d n
D n y n ≤e n
E n x n +F n y n ＝f n
G n y n ≤p n
Wherein x and y are decision variables, and a, b, c, d and p are column vectors of an objective function and a constraint condition respectively; A. b, C, D, E, F, G represents a coefficient matrix of constraints. The first-stage objective function comprises an energy storage system, controllable loads and running cost of air conditioner flexible resources, and the second-stage objective function comprises electricity purchasing and selling cost and photovoltaic unit running cost. And the maximum output value of the photovoltaic unit is a predicted value corresponding to each time period in the deterministic optimization model.
Because of various uncertain factors in the main body of each generator, the prediction accuracy of the output of the photovoltaic generator set is difficult to ensure. Thus, the scheduling operation plan derived from the deterministic optimization model may not be able to address the problems caused by the uncertainty. The invention introduces a polyhedral uncertainty set to describe the uncertainty of the output of the photovoltaic unit.
In the middle ofAnd (5) an uncertainty set of the output of the photovoltaic unit. />The uncertainty adjustment parameter is used for adjusting the conservation degree of the main body operation scheme of the producer and the consumer. When the uncertain adjustment parameters are set smaller, the time period that the allowable photovoltaic unit output reaches the uncertainty set boundary is reduced, and the two-stage robust optimization decision model of the producer and the consumer is converted into the following form.
s.t.(15b)-(15f)
Preferably, in the step 4, the two-stage robust optimization decision model of the producer and the consumer is solved, the characteristics that the two-stage robust optimization model is solved and needs dual are considered, the flexible resource decision quantity such as the internal energy storage charge and discharge quantity, the controllable load adjustment quantity, the air conditioner electricity utilization adjustment quantity and the like of the producer and the consumer is set as a first-stage decision variable, the purchase and sales quantity in the community micro-grid sharing transaction market and the output value of the photovoltaic unit are set as a second-stage variable, and the two-stage decision variable is divided into a main problem and a sub problem for characterization:
according to the dual principle, the max-min problem of the atomic problem SP can be converted into the max problem.
Wherein the method comprises the steps ofThen the corresponding dual variables are, wherein +.>As nonlinear terms, the Big-M method is required to be applied to linearize the sub-problem,
the two-order robust optimization decision model of the producer and the consumer adopts a column and constraint generation algorithm to carry out iterative solution on the main problem MP and the sub-problem SP, and the specific solution steps are as follows.
The first step: initializing related variables, taking ub=1e8, lb= -1e8, s=1, epsilon 1 ＝0.01,Γ；
And a second step of: solving the main problem to obtain a decision junctionFruit setUpdating lower bound
And a third step of: according to the main problem resultSolving the sub-problem to obtain a decision result +.>Then update the upper bound ++>If UB is s -LB s ≤ε 1 Stopping iteration, outputting an optimization decision result, and otherwise, jumping to the fourth step.
Fourth step: updating s=s+1, and then turning to the second step;
the specific pricing steps are known from the solving steps as follows:
the first step: initializing a producer and consumer main body in a community micro-grid to share transaction initial electricity price and iteration convergence conditions;
and a second step of: according to the received shared transaction electricity price of the producers and consumers in the community micro-grid, solving the flexible resource operation plan of the producers and consumers by adopting a column and constraint generation algorithm;
and a third step of: calculating the supply-demand ratio of each period of the community micro-grid and the sharing transaction time-sharing electricity price according to the received purchase and sales electricity quantity of the consumer body in the sharing transaction market of the community micro-grid;
fourth step: judging whether the convergence condition is met, if the market sharing trading electricity price deviation of the two previous and subsequent decisions meets the convergence condition, outputting a decision result, otherwise, returning to the second step.
By adopting the technical scheme, each producer and consumer can adjust the operation plan of internal flexible resources and the purchase and sales electricity quantity in the shared market according to the transaction price of the shared market in the community micro-grid, meanwhile, the community micro-grid energy coordination management main body can calculate the supply and demand ratio of each operation period of the community micro-grid according to the purchase and sales electricity quantity of the producer and consumer in each operation period, adjust the shared transaction price in the community micro-grid, finally determine the shared transaction time-sharing electricity price of the producers and consumers in the community micro-grid through loop iteration, determine the shared transaction time-sharing electricity price of the producers and consumers in the community micro-grid through an iteration solving framework, wherein a robust optimization decision model of each producer and consumer main body adopts a column and constraint decomposition algorithm to carry out iteration solving, and a decision model of the producer and consumer main body adopts the existing solving tool package CPLEX to carry out effective solving.
The beneficial effects of the invention are as follows:
1. the sharing transaction framework of the multiple producers and consumers in the community micro-grid is constructed, a time-sharing electricity price mechanism considering the supply and demand ratio of the community micro-grid is designed, and the energy sharing among the producers and consumers is promoted by exciting the producers and consumers to change the operation plan of flexible resources such as internal controllable load, energy storage and the like.
2. The risk possibly caused by the uncertainty of the output of the photovoltaic unit in the generator and the generator main body to participate in the transaction is considered, a two-stage robust optimization decision model of the generator and generator main body is constructed, the main problem and the sub problem of model decomposition are solved in an iterative mode by using a column and constraint generation algorithm, and the existing solution tool package CPLEX is adopted for effective solution.
Drawings
FIG. 1 is a community micro-grid system architecture;
FIG. 2 is a photovoltaic unit output and community microgrid outdoor temperature prediction scenario;
energy requirements of producers and consumers in Case 1 and Case 2 of fig. 3;
FIG. 4 details of the electric power transactions of the community micro-grid with the power distribution network operators;
FIG. 5 sharing transaction time-of-use electricity prices within a community micro-grid;
FIG. 6 is a run result of internal flexible resources of the producer;
FIG. 7 is a view of the amount of waste light from the photovoltaic unit inside the generator;
FIG. 8 illustrates a shared transaction price convergence result within a community micro-grid;
fig. 9 is a flow chart of a method.
Detailed Description
The technical solution of the present invention will be described in further detail with reference to the accompanying drawings, but the scope of the present invention is not limited to the following description.
As shown in fig. 9, the invention focuses on constructing a community micro-grid multi-producer and multi-consumer sharing transaction framework, and elaborates a time-of-use pricing method for promoting the sharing of energy sources of the community micro-grid multi-producer and multi-consumer, wherein a multi-producer and multi-consumer sharing transaction time-of-use electricity price mechanism in the community micro-grid is determined by adopting an iteration solving framework of an embedded column and constraint generation algorithm.
Assuming that the specific constitution of the community micro-grid system is shown in figure 1, different producers and consumers may contain different flexible resources, wherein the operation parameters of the different flexible resources are shown in table 1, the predicted scene of the photovoltaic unit in the main body of the different producers and consumers and the outdoor temperature values of different operation periods are shown in figure 2, and lambda is based on the internet power price of China sell And lambda (lambda) buy Set to 0.4 and 1. Mu.m/kWh, respectively.
TABLE 1 Flexible resource operation parameters
According to the community micro-grid system time-of-use electricity price mechanism, simulation is carried out on the promotion effect of sharing transactions of producers and consumers, and the simulation situation of independent operation of each producer and consumer of the community micro-grid system is adopted to compare with the energy sharing mechanism of promoting the community micro-grid multiple producers and consumers, which is provided by the patent, and the simulation situation is not analyzed, and is marked as Case 2, and the model provided by the patent is marked as Case 1. Wherein the uncertainty of the photovoltaic unit adjusts the parameter Γ PV And the maximum fluctuation range of the photovoltaic unit upwards and downwards is 10 percent by setting the photovoltaic unit as 4.
The simulation is carried out according to the simulation scheme, and the energy requirements of producers and consumers in the community micro-grid and the total net requirements of the community micro-grid are shown in Case 1 and Case 2 as shown in fig. 3. Because the output characteristics of the photovoltaic power generation units inside different producers and consumers are similar, the photovoltaic power generation units in 8:00, 9:00, 16:00-17:00 are in low power generation periods, and the photovoltaic power generation units in 10:00-15:00 are in high power generation periods. The total power exchange results between the community micro-grid and the distribution network operators in Case 1 and Case 2 are shown in fig. 4. The comparison shows that the proposed energy sharing strategy for producers and consumers in the community micro-grid can reduce the energy dependence on the main power grid and promote the on-site utilization of renewable energy.
Because the producers and consumers can purchase electric energy at a lower price in the community micro-grid sharing transaction market and sell the rest electric energy at a higher price, the running cost of the producers and consumers in the community micro-grid is reduced, and the running cost of each producer and consumers and the percent of saving compared with Case 2 are shown in the table 2. It can be seen that the running costs of the 4 producer and consumer subjects were reduced by 19.1%, 10.1%, 11.1%, 40.5% and 16.1%, respectively. The SDR and internal sharing transaction time-of-use electricity price results of each running time period of the community micro-grid are shown in figure 5. Because 9:00-16:00 photovoltaic units generate higher power, SDR of the community micro-grid is relatively higher, and the internal sharing transaction price in the operation time periods is relatively lower.
TABLE 2 running costs for the product and the product
The sharing transaction time-sharing electricity price based on the supply-demand ratio of the community micro-grid can guide the controllable load to increase consumption when the power generation of the photovoltaic unit is sufficient, guide the energy storage system to charge when the power generation of the photovoltaic unit is sufficient, and discharge when the load demand is large. The flexible resource operation results are shown in fig. 6. Fig. 6 (a) shows the change of the indoor temperature around the most comfortable indoor reference temperature, and the power consumption of the hvac is mainly arranged in a low price period, precooling the indoor temperature. The results of the operation of the load transferable inside the producer 2 and the consumer 3 are shown in fig. 6 (b) and 6 (c). The producer and consumer bodies 2, 3 transfer their partial flexible loads from 8-10 run periods and 17-period low-photovoltaic-unit power generation to 11-16 run periods high-photovoltaic-unit power generation periods. As shown in fig. 6 (d), the consumer body 4 may purchase the remaining electrical energy from the other consumer bodies and store it in the energy storage system and then discharge it from the energy storage system to provide electrical energy to the other consumer bodies. Simulation results show that the time-sharing pricing method based on the supply-demand ratio of the community micro-grid can guide flexible resource operation inside producers and consumers, increase in-situ consumption of renewable energy sources inside the community micro-grid, and promote energy sharing among the producers and consumers.
In order to further analyze the applicability of the two-stage adaptive robust optimization decision model under different uncertainty adjustment parameters, an uncertainty adjustment parameter Γ is set PV The results of the optimization decisions for the 4 producer and consumer subjects when changing from 2 to 10 are shown in figure 7. The maximum output value of the photovoltaic unit is reduced, the power of electricity selling of the producer and the consumer is also reduced, and the power of the photovoltaic unit is reducedThe lower limit thereof is reached in more time periods.
Then, a comparative study was performed on the robust optimization model and the stochastic optimization model. For different uncertainty adjustment parameters Γ PV And generating 1000 scenes from the uncertainty set by using a Monte Carlo simulation method, and respectively making decisions by using a random optimization method in 4 producer and consumer bodies. The results of the comparative runs of the robust optimization decision and the stochastic programming method are shown in table 3. Because of the conservation of the robust optimization method, the result of the optimized operation based on the random programming is smaller than the decision result based on the robust optimized operation. But the difference between them follows Γ PV And decreases with increasing numbers. However, the decision result based on the stochastic programming method has a greater running cost in the worst scenario than the result based on the robust optimization decision. For the producer and consumer bodies, the decision model based on the robust optimization method is more effective than the optimization decision model based on the stochastic programming method, especially in the face of large uncertainty of the photovoltaic unitIn this case.
TABLE 3 optimization decision results based on robust optimization and stochastic programming
The simulation operation platform is a personal computer and is configured as 16GB RAM and Intel-i7CPU. All optimization decision models were simulated in MATLAB 2016a embedded in CPLEX 12.6. The number of iterations and calculation time for the 4 producer-consumer example systems and the 10 producer-consumer example systems to reach the set convergence condition are given in table 3. Deviations based on the 4 producer and consumer example system internal sharing transaction prices are shown in fig. 9. In the 4 producer-consumer computing systems and the 10 producer-consumer computing systems, the whole iterative decision algorithm can reach the set convergence condition of 0.001 only at 79.7s and 189.1s (iterated 5 times and 7 times). The calculation results of the two example systems show that the problem of energy sharing of multiple producers and consumers in the community micro-grid can be effectively solved by embedding the columns and the iterative solution framework of the constraint generation algorithm.
TABLE 4 System simulation run results based on 4 and 10 producers/consumers composition
The foregoing is merely a preferred embodiment of the invention, and it should be understood that the described embodiments are some, but not all, of the embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention. The invention is not limited to the forms disclosed herein, but is not to be construed as limited to the embodiments set forth herein, but is capable of use in various other combinations, modifications and environments and is capable of changes within the scope of the inventive concept, either as a result of the foregoing teachings or as a result of the knowledge or skills in the relevant art. And that modifications and variations which do not depart from the spirit and scope of the invention are intended to be within the scope of the appended claims.

Claims (2)

1. A time-sharing pricing method for promoting energy sharing of multiple producers and consumers in a community micro-grid is characterized by comprising the following steps of
Step 1, analyzing characteristics of sharing transaction markets of multiple-yield consumers in a community micro-grid, and constructing a sharing transaction framework of the multiple-yield consumers in the community micro-grid;
step 2, aiming at a sharing transaction framework of the multi-product and the consumer in the community micro-grid, designing a sharing transaction time-of-use electricity price mechanism of the multi-product and the consumer in the community micro-grid;
step 3, modeling the internal flexible resources of the producer and the consumer, and constructing a producer and consumer main body market decision model based on a two-stage robust model;
step 4, solving a shared transaction time-of-use electricity price mechanism of the multi-producer and the consumer in the community micro-grid through an iteration solving framework embedded with a column and constraint generating algorithm;
in the step 2, aiming at the sharing transaction framework of the multi-product and multi-product consumers in the community micro-grid, designing a sharing transaction time-sharing electricity price mechanism of the multi-product and multi-consumer in the community micro-grid comprises the steps of reflecting the surplus and shortage situation of the electric energy of the multi-product and multi-consumer in the community micro-grid at each moment by introducing a supply-demand ratio, wherein the supply-demand ratio is defined as follows:
in the middle ofThe sum of electricity purchasing power of all electricity-deficient consumers in the community micro-grid at the t time period is->The electricity price of sharing transaction electricity selling among producers and consumers in the community micro-grid is as follows for the sum of electricity selling of all surplus electricity producing and consuming consumers in the community micro-grid at the t period
Wherein lambda is the compensation electricity price,electricity price purchased from distribution network operators for producers and consumers in community micro-grid, +.>The method comprises the steps of (1) surfing electricity prices for surplus electricity of producers and consumers in a community micro-grid;
the sharing transaction electricity purchasing price among the consumers in the community micro-grid is as follows:
modeling the internal flexibility resources of the producer and the consumer, and constructing a producer and consumer main body market decision model based on a two-stage robust model comprises the following contents:
objective function of the producer and consumer body market decision model:
the objective function comprises electricity purchasing and selling cost, air conditioning and load-transferable adjustment cost, operation cost of an energy storage system and operation cost of a photovoltaic unit in the community micro-grid energy sharing market, and the detailed calculation formula is as follows:
in the method, in the process of the invention,the running cost coefficients of the air conditioner, the transferable load, the energy storage system and the photovoltaic system are respectively,
the operation constraint of the air conditioner is as follows:
the air conditioner is a heating ventilation air conditioner, and according to the indoor and outdoor temperature transformation law, the relation between the power and the temperature of the air conditioner and the range constraint of maintaining the indoor temperature are considered, whereinAnd->Indoor and outdoor temperatures, η n And R is n Heating capacity and thermal resistance of the heating, ventilation and air conditioning unit respectively, < >>The operation power of the heating ventilation air conditioning unit;
the operational constraints of the transferable loads are:
wherein the method comprises the steps ofFor a load transferable predictive value, +.>For the adjusted value, +.>Is the maximum adjustment proportion;
the operation constraint of the energy storage system is as follows:
wherein;the charging and discharging state is a charging and discharging state of the energy storage system in a certain time period; wherein->Charge-discharge power per unit operation period, P i ess,max Maximum charge and discharge power of the energy storage system in unit time; wherein->For the charge of a certain period of time of the energy storage system, < ->Is the charge and discharge efficiency of the energy storage system +.>Maximum and minimum charge amounts for the energy storage system;
output constraint of the photovoltaic unit:
the output value of the photovoltaic unit is smaller than the predicted scene, whereinIs practical for a photovoltaic unitA force value;
the electricity purchasing constraint of the main body of the producing and eliminating person:
wherein the method comprises the steps ofFor the electricity purchasing state of the body of the producing and eliminating person, < ->Sharing the maximum transaction electric quantity of the transaction market with the community micro-grid for each operation period of the producer and the consumer;
the producer-consumer body internal power balance constraint:
in any time period, the electricity purchasing quantity of the producer and the consumer body, the photovoltaic output value, the energy storage and discharge quantity and the load electricity consumption quantity are balanced;
the deterministic optimization decision model of the producer and the consumer is expressed in the following matrix form;
s.t.A n x n ≤c n
B n x n ＝0
C n y n ≤d n
D n y n ≤e n
E n x n +F n y n ＝f n
G n y n ≤p n
wherein x and y are decision variables, and a, b, c, d, e, f and p are column vectors of an objective function and a constraint condition respectively; A. b, C, D, E, F, G the coefficient matrix of the constraint condition, wherein the objective function of the first stage comprises the running cost of the energy storage system, the controllable load and the flexible resource of the air conditioner, and the objective function of the second stage comprises the electricity purchasing cost and the running cost of the photovoltaic unit; the maximum output value of the photovoltaic unit is a predicted value corresponding to each time period in the deterministic optimization model:
introducing a polyhedral uncertainty set to describe uncertainty of output of the photovoltaic unit:
in the middle ofFor the uncertainty set of the output of the photovoltaic unit, < +.>For "uncertainty adjustment parameters" for adjusting the producer-consumer main body operating schemeThe conservation degree of the product and the eliminator main body two-stage robust optimization decision model is converted into the following form:
s.t.(15b)-(15f)
；
in the step 4, the two-stage robust optimization decision model of the producer and the consumer is solved, the characteristics that the two-stage robust optimization model is solved and needs dual are considered, the decision quantity of active resources such as the internal energy storage charge and discharge quantity of the producer and the consumer, the transferable load adjustment quantity, the air conditioner power consumption adjustment quantity and the like are set as a first-stage decision variable, the purchase and sales quantity in the community micro-grid sharing transaction market and the output value of the photovoltaic unit are set as a second-stage variable, and the two-stage decision variable is divided into a main problem and a sub-problem for characterization:
according to the dual principle, the max-min problem of the atomic problem SP can be converted into the max problem;
wherein the method comprises the steps ofThen the corresponding dual variables are, wherein +.>As nonlinear terms, the Big-M method is required to be applied to linearize the sub-problem,
the two-order robust optimization decision model of the producer and the consumer adopts a column and constraint generation algorithm to carry out iterative solution on the main problem MP and the sub-problem SP, and the specific solution steps are as follows:
the first step: initializing related variables, taking ub=1e8, lb= -1e8, s=1, epsilon 1 ＝0.01,Γ；
And a second step of: solving the main problem to obtain a decision resultUpdating lower bound->
And a third step of: according to the main problem resultSolving the sub-problem to obtain a decision result +.>Then updating the upper bound valueIf UB is s -LB s ≤ε 1 Stop the stackOutputting an optimization decision result, otherwise jumping to the fourth step;
fourth step: update s=s+1 and then go to the second step.
2. The time-sharing pricing method for promoting energy sharing of multiple-yield and multiple-yield consumers in the community micro-grid according to claim 1, wherein in the step 1, characteristics of the sharing transaction market of the multiple-yield and multiple-yield consumers in the community micro-grid are analyzed, constructing a framework of the sharing transaction of the multiple-yield and multiple-yield consumers in the community micro-grid comprises organizing the participation of a consumer body in the sharing transaction market of the energy sharing market of the community micro-grid, collecting purchase and sales electricity quantity of the consumer in the sharing transaction market of the energy, and determining and issuing the transaction time-sharing electricity price of the consumer body in the sharing market of the energy.
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