CN106355344A - Method for robustly and optimally operating micro-grids on basis of orthogonal arrays - Google Patents
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Abstract
The invention discloses a method for robustly and optimally operating micro-grids on the basis of orthogonal arrays. The method includes steps of extracting static data of micro grid architectures, power types, operation costs of the power types, energy storage system unit operation cots, interaction costs, time-of-use electricity prices and the like; building micro-grid uncertainty set models; screening test scenarios; building micro-grid robust and optimal operation models on the basis of the orthogonal arrays and designing solution strategies on the basis of the test scenarios so as to obtain ultimate micro-grid robust and optimal operation schemes. The method has the advantages that the grid-connection micro-grids with consideration of output of renewable energy distributed power sources and load demand uncertainty can be optimally operated by the aid of the method, and dispatching reference can be provided for operation personnel of the micro-grids.
Description
Technical Field
The invention relates to a micro-grid robust optimization operation method based on an orthogonal array, and belongs to the technical field of optimization scheduling and operation of power systems.
Background
Compared with the regulation and control of the non-renewable energy distributed power supply, the power generation form of the renewable energy distributed power supply is easily influenced by factors such as climate and environment, obvious randomness and intermittency are achieved, uncertainty in operation of a power distribution system is inevitably increased by large-scale access of the system, and restriction relation between targets and constraints is more complex in research and modeling. How to adapt to uncertain working conditions of output and load requirements of various renewable energy distributed power supplies and realize benign interaction and economic operation of multi-element resources is a research difficulty in energy management and optimization of a micro-grid. Therefore, how to effectively establish a multi-period economic model and guide and realize a robust operation plan of the regional unit by combining the severe scene target with the largest interaction cost becomes an important problem to be solved urgently by a dispatching department.
Disclosure of Invention
The invention aims to provide a micro-grid robust optimization operation method based on an orthogonal array, and the optimization configuration of renewable energy distributed power sources and distribution system resources with load uncertainty is realized.
In order to achieve the above object, the present invention provides a microgrid robust optimization operation method based on an orthogonal array, comprising the steps of:
(1) extracting static data such as a micro-grid architecture, a power type and operation cost thereof, unit operation cost of an energy storage system, interaction cost, time-of-use electricity price and the like;
(2) constructing an uncertain set of output and load requirements of the renewable energy distributed power supply;
(3) screening a robust test scene based on an orthogonal array;
(4) constructing a micro-grid robust optimization operation model;
(5) and designing a two-stage solving strategy based on a test scene to obtain a final micro-grid robust optimization operation scheme.
2. The microgrid architecture comprising: the power supply type, the distributed energy storage system, the power load, the dispatching control center and the superior power grid interface.
3. The distributed power types include: non-renewable energy based distributed power sources and renewable energy based distributed power sources.
4. The interaction cost model represents an economic cost resulting from an interaction power transfer between the microgrid and a superordinate power grid.
5. The uncertain set construction steps of the output and load requirements of the renewable energy distributed power supply are as follows:
(1) determining upper and lower boundary reference quantities of an output uncertain set of the renewable energy distributed power supply according to output historical data of the distributed power supply:
correcting the upper and lower output boundary values according to the operation constraint of the actual renewable energy distributed power supply unit:
in the formula,、respectively are the upper and lower boundary reference values of the output of the renewable energy distributed power supply,、respectively providing upper and lower boundary reference values for the output of the modified renewable energy distributed power supply,distributed power output for renewable energyThe base value of the point of force prediction,in order to predict the error probability density function,is composed ofThe method of expressing the inverse function of (a),、respectively the maximum and minimum output of the renewable energy distributed power supply,in order to be a confidence level parameter,、respectively as upper and lower threshold values of the confidence level parameter;
(2) thus, an indeterminate set of distributed power sources is formed:
the same uncertainty set of available load demands is:
in the formula,as renewable energy sourcesDistributed power supply in time slotThe actual force to be exerted is,in time slots for load demandsThe actual value of the demand for (c) is,in time slots for load demandsThe base value of the point prediction is set,、respectively at time intervals for load demandUpper and lower boundary reference values of (1).
6. The robust test scene screening based on the orthogonal array comprises the following steps:
(1) dividing a scheduling cycle into T time intervals, wherein the distributed renewable energy output has T discrete values in the scheduling cycle, and the T discrete values are recorded as:the load demand has T discrete values in the scheduling period, and the T discrete values are recorded as:therefore, the input parameters of the renewable energy type distributed power supply and the load demand are 2 × T in total in one scheduling period;
(2) screening a test scene: screening through an orthogonal array and a corresponding parameter value horizontal assignment rule;
the Orthogonal Array (OA) matrix refers to an A × B matrix composed of different input parameters corresponding to C, and an orthogonal array of intensities D (0 ≦ D ≦ B), if any of the A × D sub-matrices of the matrix A × B, the arrangement of any intensity D is exactly as in the case of the matrix A × BAppearing in each row, noted:
wherein, A is the size of the matrix array, and is used for referring to the number of scenes to be tested under the current input parameter value level; b is the total number of parameters, namely the total number of the input parameters of the output and load requirements of the renewable energy distributed power supply; c is a single group of input parameters corresponding to a value level; d is the intensity coefficient of OA;
therefore, the total number of test scenes is obtained according to a plurality of groups of different input parameter value levels.
7. The micro-grid robust optimization operation model comprises the following steps:
(1) the objective function of the micro-grid robust optimization operation model is as follows:
wherein,representing the total cost of the microgrid;the unit power generation cost of the conventional generator set is；、Is a unit power generation cost coefficient, the specific value is related to the selected type of the generator and the parameters thereof,for conventional generating sets during a periodThe output of (2);for regulating and controlling the cost of the energy storage system, there are；The cost is regulated and controlled for the energy storage device unit;outputting power for the energy storage system; the general mathematical expression of interaction cost is:，，、respectively corresponding to the time intervalThe micro-grid purchases from the main network,0-1 state variable of power transmission, set whenWhen the temperature of the water is higher than the set temperature,when is coming into contact withWhen the temperature of the water is higher than the set temperature,simultaneously, the following steps are carried out:；the interaction cost under the worst scene is satisfied，sRepresenting a current test scenario;Sis the total test scenario; in an objective functionThe method is expressed by means of interaction cost and a scene set, namely a micro-grid robust optimization operation mode can be transformed into the following steps:
wherein,as a scenesThe lower comprehensive economic operation cost optimal value;
(2) the constraint conditions of the objective function of the microgrid robust optimization operation model are as follows:
the power upper and lower limit constraints which need to be met by the conventional generator set at different time intervals are as follows:
wherein,、respectively the upper limit and the lower limit of the output of the conventional generator set;
the climbing power constraint of the conventional unit is as follows:
wherein,、the power limit value is the upper and lower climbing power limit value;
when considering a multiple unit extension model (multiple units are responsible for generating power), the conventional generating set adopts the following stepsiThe power generation cost model of the unit is as follows:
wherein,for a conventional set of generator set numbers,the start-stop state of the first unit is a time period,indicating a period of timeFirst, theThe set unit is in a starting state and corresponding，Indicating a period of timeFirst, theThe set of units being in a standstill state, correspondingly；Is as followsThe starting cost of the unit;
and (3) expanding the conventional power supply types to the condition of multiple conventional generator sets, and correcting the related variable patterns:
wherein,for the unit power generation cost of multiple conventional generator sets,in order to increase the number of the conventional generator sets,is as followsThe unit power generation cost of a conventional generator set;
the relation between the charging and discharging power of the energy storage system and the capacity of the energy storage system is as follows:
wherein,the current capacity state of the energy storage device;
the energy storage system is subjected to charge and discharge power constraint and capacity constraint as follows:
wherein,、respectively is the upper and lower limits of the charging and discharging power of the energy storage device in unit time,、respectively an upper limit and a lower limit of the capacity of the energy storage device,、is the cut-off rate of charge and discharge
The constraint conditions to be met by the interaction power are as follows:
wherein,、respectively is a time interval interactive power transmission upper limit value and a time interval interactive power transmission lower limit value;
standby power constraint:
wherein,is a back-up power for the interactive power,in order to save the standby power for the conventional power generation cost,is the standby power of the energy storage system,representing the system in timeThe minimum backup power that needs to be reached is set according to the capacity of the microgrid.
8. The interaction cost is used for reflecting the consumption and utilization conditions of the renewable energy power generation resources of the multi-period system, and the influence factors of the interaction cost comprise: the micro-grid interacts power, electricity purchasing price and electricity selling price with a power grid at the upper level; wherein, the interactive power influence factor of little electric wire netting and higher level electric wire netting includes: the method comprises the steps of conventional unit cost economic indexes, purchase and sale electricity prices, interaction states and operation states of the micro-grid and a superior grid.
9. The two-stage strategy solving based on the test scene comprises the following steps:
(1) initializationTo aTaking various constraint conditions into consideration for each test scene in the system, and carrying out optimization solution to obtain each scenesIs as follows、And calculateWherein:representing an initial feasible solution of the decision variables;representing a scenesMaking a decision variable optimal solution;representing a scenesThe size of the interaction cost corresponding to the lower optimal solution;
(2) order to，According toUpdatingAnd their corresponding、Whereinrepresents the "worst" test scenario;representing the interaction cost under the worst scene of the optimal operation scheme;representing a final solution of the decision variables;represents the optimal economic operating cost considering the robust target of the worst scene;
and taking the operation scheme corresponding to the maximum interaction cost as the optimal robust operation scheme of the micro-grid.
The invention provides a robust optimization operation model and a solving method thereof for a grid-connected microgrid and under the uncertainty of the output and load requirements of a renewable energy type distributed power supply. Carrying out uncertainty interval quantification on the output and load requirements of the renewable energy distributed power supply by using an interval prediction method to generate an uncertainty set for optimizing a model; the coordinated source-storage scheduling model can improve the flexibility and the economy of the operation of the micro-grid; the method for generating the test scene by using the orthogonal array matrix is a simple and effective method for screening the simulation scene.
Drawings
FIG. 1 is a schematic diagram of an exemplary microgrid architecture of the present invention;
the attached drawings and the meanings of each reference number in the text:time of day for distributed renewable energy classesThe output power of the power converter (c),for energy storage systems during periodsThe output power of the power converter (c),for the interaction power between the regional power grid and the upper power grid,for the conventional power supply unit in the regional system to output power,is the total load demand of the system.
Detailed description of the invention
The following describes the microgrid robust optimization operation method based on the orthogonal array in further detail with reference to the accompanying drawings.
The invention provides a micro-grid robust optimization operation method based on an orthogonal array, which comprises the following steps:
(1) extracting static data such as a micro-grid architecture, a power type and operation cost thereof, unit operation cost of an energy storage system, interaction cost, time-of-use electricity price and the like;
(2) constructing an uncertain set of output and load requirements of the renewable energy distributed power supply;
(3) screening a robust test scene based on an orthogonal array;
(4) constructing a micro-grid robust optimization operation model;
(5) and designing a two-stage solving strategy based on a test scene to obtain a final micro-grid robust optimization operation scheme.
The microgrid architecture comprising: the power supply type, the distributed energy storage system, the power load, the dispatching control center and the superior power grid interface.
The distributed power types include: non-renewable energy based distributed power sources and renewable energy based distributed power sources.
The interaction cost model represents an economic cost resulting from an interaction power transfer between the microgrid and a superordinate power grid.
The uncertain set construction steps of the output and load requirements of the renewable energy distributed power supply are as follows:
(1) determining upper and lower boundary reference quantities of an output uncertain set of the renewable energy distributed power supply according to output historical data of the distributed power supply:
correcting the upper and lower output boundary values according to the operation constraint of the actual renewable energy distributed power supply unit:
in the formula,、respectively are the upper and lower boundary reference values of the output of the renewable energy distributed power supply,、respectively providing upper and lower boundary reference values for the output of the modified renewable energy distributed power supply,a base value is predicted for the output point of the renewable energy distributed power supply,in order to predict the error probability density function,is composed ofThe method of expressing the inverse function of (a),、respectively the maximum and minimum output of the renewable energy distributed power supply,in order to be a confidence level parameter,、respectively as upper and lower threshold values of the confidence level parameter;
(2) thus, an indeterminate set of distributed power sources is formed:
the same uncertainty set of available load demands is:
in the formula,distributed power for renewable energy classThe actual force to be exerted is,in time slots for load demandsThe actual value of the demand for (c) is,in time slots for load demandsThe base value of the point prediction is set,、respectively at time intervals for load demandUpper and lower boundary reference values of (1).
The robust test scene screening based on the orthogonal array comprises the following steps:
(1) dividing a scheduling cycle into T time intervals, and outputting the distributed renewable energyThere are T discrete values in the scheduling period, denoted as:the load demand has T discrete values in the scheduling period, and the T discrete values are recorded as:therefore, the input parameters of the renewable energy type distributed power supply and the load demand are 2 × T in total in one scheduling period;
(2) screening a test scene: screening through an orthogonal array and a corresponding parameter value horizontal assignment rule;
the Orthogonal Array (OA) matrix refers to an A × B matrix composed of different input parameters corresponding to C, and an orthogonal array of intensities D (0 ≦ D ≦ B), if any of the A × D sub-matrices of the matrix A × B, the arrangement of any intensity D is exactly as in the case of the matrix A × BAppearing in each row, noted:
wherein, A is the size of the matrix array, and is used for referring to the number of scenes to be tested under the current input parameter value level; b is the total number of parameters, namely the total number of the input parameters of the output and load requirements of the renewable energy distributed power supply; c is a single group of input parameters corresponding to a value level; d is the intensity coefficient of OA;
therefore, the total number of test scenes is obtained according to a plurality of groups of different input parameter value levels.
The micro-grid robust optimization operation model comprises the following steps:
(1) the objective function of the micro-grid robust optimization operation model is as follows:
wherein,representing the total cost of the microgrid;the unit power generation cost of the conventional generator set is；、Is a unit power generation cost coefficient, the specific value is related to the selected type of the generator and the parameters thereof,for conventional generating sets during a periodThe output of (2);for regulating and controlling the cost of the energy storage system, there are；The cost is regulated and controlled for the energy storage device unit;outputting power for the energy storage system; the general mathematical expression of interaction cost is:，，、respectively corresponding to the time intervalThe 0-1 state variable of the micro-grid for purchasing and transmitting power to the main grid is set whenWhen the temperature of the water is higher than the set temperature,when is coming into contact withWhen the temperature of the water is higher than the set temperature,simultaneously, the following steps are carried out:；the interaction cost under the worst scene is satisfied，sRepresenting a current test scenario;Sis the total test scenario; in an objective functionThe method is expressed by means of interaction cost and a scene set, namely a micro-grid robust optimization operation mode can be transformed into the following steps:
wherein,as a scenesThe lower comprehensive economic operation cost optimal value;
(2) the constraint conditions of the objective function of the microgrid robust optimization operation model are as follows:
the power upper and lower limit constraints which need to be met by the conventional generator set at different time intervals are as follows:
wherein,、respectively the upper limit and the lower limit of the output of the conventional generator set;
the climbing power constraint of the conventional unit is as follows:
wherein,、the power limit value is the upper and lower climbing power limit value;
when considering a multiple unit extension model (multiple units are responsible for generating power), the conventional generating set adopts the following stepsiThe power generation cost model of the unit is as follows:
wherein,for a conventional set of generator set numbers,the start-stop state of the first unit is a time period,indicating a period of timeFirst, theThe set unit is in a starting state and corresponding，Indicating a period of timeFirst, theThe set of units being in a standstill state, correspondingly；Is as followsThe starting cost of the unit;
and (3) expanding the conventional power supply types to the condition of multiple conventional generator sets, and correcting the related variable patterns:
wherein,for the unit power generation cost of multiple conventional generator sets,in order to increase the number of the conventional generator sets,is as followsThe unit power generation cost of a conventional generator set;
the relation between the charging and discharging power of the energy storage system and the capacity of the energy storage system is as follows:
wherein,the current capacity state of the energy storage device;
the energy storage system is subjected to charge and discharge power constraint and capacity constraint as follows:
wherein,、respectively is the upper and lower limits of the charging and discharging power of the energy storage device in unit time,、respectively an upper limit and a lower limit of the capacity of the energy storage device,、is the charge-discharge cut-off rate;
the constraint conditions to be met by the interaction power are as follows:
wherein,、respectively is a time interval interactive power transmission upper limit value and a time interval interactive power transmission lower limit value;
standby power constraint:
wherein,is a back-up power for the interactive power,in order to save the standby power for the conventional power generation cost,is the standby power of the energy storage system,representing the system in timeThe minimum backup power that needs to be reached is set according to the capacity of the microgrid.
The interaction cost is used for reflecting the consumption and utilization conditions of the renewable energy power generation resources of the multi-period system, and the influence factors of the interaction cost comprise: the micro-grid interacts power, electricity purchasing price and electricity selling price with a power grid at the upper level; wherein, the interactive power influence factor of little electric wire netting and higher level electric wire netting includes: the method comprises the steps of conventional unit cost economic indexes, purchase and sale electricity prices, interaction states and operation states of the micro-grid and a superior grid.
The two-stage strategy solving based on the test scene comprises the following steps:
(1) initializationTo aTaking various constraint conditions into consideration for each test scene in the system, and carrying out optimization solution to obtain each scenesIs as follows、And calculateWherein:representing an initial feasible solution of the decision variables;representing a scenesMaking a decision variable optimal solution;representing a scenesThe size of the interaction cost corresponding to the lower optimal solution;
(2) order to，According toUpdatingAnd their corresponding、Whereinrepresents the "worst" test scenario;representing the interaction cost under the worst scene of the optimal operation scheme;representing a final solution of the decision variables;represents the optimal economic operating cost considering the robust target of the worst scene;
and taking the operation scheme corresponding to the maximum interaction cost as the optimal robust operation scheme of the micro-grid.
The above-described embodiments of the present invention are intended to illustrate the objects, aspects and advantages of the present invention in further detail, and it should be understood that the above-described embodiments are merely exemplary of the present invention and are not intended to limit the scope of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (9)
1. A micro-grid robust optimization operation method based on an orthogonal array is characterized by comprising the following steps:
(1) extracting static data such as a micro-grid architecture, unit operation cost of a distributed power supply, unit operation cost of an energy storage system, interaction cost, time-of-use electricity price and the like;
(2) constructing an uncertain set of output and load requirements of the renewable energy distributed power supply;
(3) screening a robust test scene based on an orthogonal array;
(4) constructing a micro-grid robust optimization operation model;
(5) and designing a two-stage solving strategy based on a test scene to obtain a final micro-grid robust optimization operation scheme.
2. The robust optimized operation method of the microgrid based on an orthogonal array as claimed in claim 1, wherein the microgrid architecture comprises: the system comprises a distributed power supply, a distributed energy storage system, a power load, a dispatching control center and a superior power grid interface.
3. The robust optimized operation method for the microgrid based on the orthogonal array as claimed in claim 1, wherein the distributed power supply types comprise: non-renewable energy based distributed power sources and renewable energy based distributed power sources.
4. The microgrid robust optimization operation method based on an orthogonal array is characterized in that the interaction cost model represents economic cost generated by interaction power transmission between a microgrid and an upper-level power grid.
5. The microgrid robust optimization operation method based on an orthogonal array of claim 1, wherein the uncertain set construction steps of output and load requirements of the renewable energy distributed power supply are as follows:
(1) determining upper and lower boundary reference quantities of an output uncertain set of the renewable energy distributed power supply according to output historical data of the distributed power supply:
correcting the upper and lower output boundary values according to the operation constraint of the actual renewable energy distributed power supply unit:
in the formula,、respectively are the upper and lower boundary reference values of the output of the renewable energy distributed power supply,、respectively providing upper and lower boundary reference values for the output of the modified renewable energy distributed power supply,a base value is predicted for the output point of the renewable energy distributed power supply,in order to predict the error probability density function,is composed ofThe method of expressing the inverse function of (a),、respectively the maximum and minimum output of the renewable energy distributed power supply,in order to be a confidence level parameter,、respectively as upper and lower threshold values of the confidence level parameter;
(2) thus, an indeterminate set of distributed power sources is formed:
the same uncertainty set of available load demands is:
in the formula,distributed power for renewable energy classThe actual force to be exerted is,in time slots for load demandsThe actual value of the demand for (c) is,in time slots for load demandsThe base value of the point prediction is set,、respectively at time intervals for load demandUpper and lower boundary reference values of (1).
6. The microgrid robust optimization operation method based on an orthogonal array is characterized in that the orthogonal array based robust test scenario screening step is as follows:
(1) dividing a scheduling cycle into T time intervals, wherein the distributed renewable energy output has T discrete values in the scheduling cycle, and the T discrete values are recorded as:the load demand has T discrete values in the scheduling period, and the T discrete values are recorded as:therefore, the input parameters of the renewable energy type distributed power supply and the load demand are 2 × T in total in one scheduling period;
(2) screening a test scene: screening through an orthogonal array and a corresponding parameter value horizontal assignment rule;
the Orthogonal Array (OA) matrix refers to an A × B matrix composed of different input parameters corresponding to C, and an orthogonal array of intensities D (0 ≦ D ≦ B), if any of the A × D sub-matrices of the matrix A × B, the arrangement of any intensity D is exactly as in the case of the matrix A × BAppearing in each row, noted:
wherein, A is the size of the matrix array, and is used for referring to the number of scenes to be tested under the current input parameter value level; b is the total number of parameters, namely the total number of the input parameters of the output and load requirements of the renewable energy distributed power supply; c is a single group of input parameters corresponding to a value level; d is the intensity coefficient of OA;
therefore, the total number of test scenes is obtained according to a plurality of groups of different input parameter value levels.
7. The microgrid robust optimization operation method based on an orthogonal array is characterized in that the microgrid robust optimization operation model is as follows:
(1) the objective function of the micro-grid robust optimization operation model is as follows:
wherein,representing the total cost of the microgrid;the unit power generation cost of the conventional generator set is；、Is a unit power generation cost coefficient, specifically value and selectedThe type of generator and its parameters are related,for conventional generating sets during a periodThe output of (2);for regulating and controlling the cost of the energy storage system, there are；The cost is regulated and controlled for the energy storage device unit;outputting power for the energy storage system; the general mathematical expression of interaction cost is:，，、respectively corresponding to the time intervalThe 0-1 state variable of the micro-grid for purchasing and transmitting power to the main grid is set whenWhen the temperature of the water is higher than the set temperature,when is coming into contact withWhen the temperature of the water is higher than the set temperature,simultaneously, the following steps are carried out:；the interaction cost under the worst scene is satisfied，sRepresenting a current test scenario;Sis the total test scenario; in an objective functionThe method is expressed by means of interaction cost and a scene set, namely a micro-grid robust optimization operation mode can be transformed into the following steps:
wherein,as a scenesThe lower comprehensive economic operation cost optimal value;
(2) the constraint conditions of the objective function of the microgrid robust optimization operation model are as follows:
the power upper and lower limit constraints which need to be met by the conventional generator set at different time intervals are as follows:
wherein,、respectively the upper limit and the lower limit of the output of the conventional generator set;
the climbing power constraint of the conventional unit is as follows:
wherein,、the power limit value is the upper and lower climbing power limit value;
when considering a multiple unit extension model (multiple units are responsible for generating power), the conventional generating set adopts the following stepsiThe power generation cost model of the unit is as follows:
wherein,for a conventional set of generator set numbers,the start-stop state of the first unit is a time period,indicating a period of timeFirst, theThe set unit is in a starting state and corresponding，Indicating a period of timeFirst, theThe set of units being in a standstill state, correspondingly；Is as followsThe starting cost of the unit;
and (3) expanding the conventional power supply types to the condition of multiple conventional generator sets, and correcting the related variable patterns:
wherein,for the unit power generation cost of multiple conventional generator sets,in order to increase the number of the conventional generator sets,is as followsThe unit power generation cost of a conventional generator set;
the relation between the charging and discharging power of the energy storage system and the capacity of the energy storage system is as follows:
wherein,the current capacity state of the energy storage device;
the energy storage system is subjected to charge and discharge power constraint and capacity constraint as follows:
wherein,、respectively is the upper and lower limits of the charging and discharging power of the energy storage device in unit time,、respectively an upper limit and a lower limit of the capacity of the energy storage device,、is the charge-discharge cut-off rate;
the constraint conditions to be met by the interaction power are as follows:
wherein,、respectively is a time interval interactive power transmission upper limit value and a time interval interactive power transmission lower limit value;
standby power constraint:
wherein,is a back-up power for the interactive power,in order to save the standby power for the conventional power generation cost,is the standby power of the energy storage system,representing the system in timeThe minimum backup power that needs to be reached is set according to the capacity of the microgrid.
8. The microgrid robust optimization operation method based on an orthogonal array as claimed in claim 7, wherein the interaction cost is used for reflecting the consumption and utilization conditions of renewable energy power generation resources of a multi-period system, and the influence factors include: the micro-grid interacts power, electricity purchasing price and electricity selling price with a power grid at the upper level; wherein, the interactive power influence factor of little electric wire netting and higher level electric wire netting includes: the method comprises the steps of conventional unit cost economic indexes, purchase and sale electricity prices, interaction states and operation states of the micro-grid and a superior grid.
9. The microgrid robust optimization operation method based on an orthogonal array is characterized in that the two-stage solution strategy based on the test scenario comprises the following steps:
(1) initializationTo aTaking various constraint conditions into consideration for each test scene in the system, and carrying out optimization solution to obtain each scenesIs as follows、And calculateWherein:representing an initial feasible solution of the decision variables;representing a scenesMaking a decision variable optimal solution;representing a scenesThe size of the interaction cost corresponding to the lower optimal solution;
(2) order to，According toUpdatingAnd their corresponding、Whereinrepresents the "worst" test scenario;representing the interaction cost under the worst scene of the optimal operation scheme;representing a final solution of the decision variables;represents the optimal economic operating cost considering the robust target of the worst scene;
and taking the operation scheme corresponding to the maximum interaction cost as the optimal robust operation scheme of the micro-grid.
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