CN111245027B - Alternating current/direct current hybrid system optimal scheduling method considering PET loss - Google Patents
Alternating current/direct current hybrid system optimal scheduling method considering PET loss Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B10/00—Integration of renewable energy sources in buildings
- Y02B10/10—Photovoltaic [PV]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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Abstract
The invention discloses an alternating current-direct current hybrid system optimization scheduling method considering PET loss, which is used for establishing an alternating current-direct current hybrid system model considering PET loss, and comprises a PET optimization model considering loss, a micro gas turbine model, an energy storage battery model, a fan model and a photovoltaic model; and setting system balance constraint by taking the minimum system running cost as a target, and optimally scheduling the alternating current-direct current hybrid system considering PET loss. The method can provide reference for the optimal scheduling of the alternating current-direct current hybrid system considering the PET loss, analyzes the influence of the PET and the energy storage equipment model on the power loss in the operation process, and has important significance for researching the influence of the PET electric energy conversion efficiency on the optimal scheduling of the alternating current-direct current hybrid system.
Description
Technical Field
The invention belongs to the technical field of power system AC/DC hybrid micro-grid optimal scheduling, and particularly relates to an AC/DC hybrid system optimal scheduling method considering PET loss.
Background
The economic and social development is not separated from the continuous and effective energy supply. By 2035, the energy demand of China is expected to be 24% of the total energy demand of the world, and the energy demand continues to be increased at a high speed, so that the contradiction between energy shortage and economic development is increasingly sharp, and the energy problem becomes the primary problem of sustainable development of China. The full-power improvement of the energy utilization efficiency is a necessary way for realizing sustainable development, and the distributed energy is successfully commercialized, and is the utilization mode with highest comprehensive efficiency, so the full-power development of the distributed energy is significant for improving the energy utilization efficiency of China.
The distributed energy access power grid is divided into two types, namely alternating current access and direct current access. Compared with an alternating current access mode, direct current access does not need conversion between direct current and alternating current, the conversion process between the direct current and the alternating current is saved, on one hand, the cost of the conversion equipment is saved, and the loss is reduced compared with the original structure because no conversion link is arranged; on the other hand, the phase and frequency synchronization in the AC access mode is not needed to be considered any more in the DC access power grid, and the controllability and the reliability of the system can be enhanced theoretically. For the above reasons, the dc access mode is getting more and more attention, and is considered as an ideal access mode for distributed energy. However, considering the historical development of the power system, in the present stage, the main form of the power grid is also an alternating current network, and it is unlikely to change the power grid into direct current in a short period, and the main form of the distributed energy grid connection is also an alternating current form, so that the hybrid structure of the alternating current and the direct current will be the main system form for a long period later.
The large-scale distributed energy access power system is not realized by simply connecting the distributed energy with the system, because the distributed energy is constrained by various conditions of solar energy and wind energy, the power generation of the distributed energy is intermittent, a large amount of access can cause disturbance to the power system, and the flexible regulation and control and interconnection capacity of the current power grid are not enough to solve the problems, so the large-scale access of the distributed energy is blocked, and the wind and light discarding phenomenon is caused. PET has flexible power regulation and control capability, and can be applied to an alternating current-direct current hybrid system containing distributed energy sources to solve the problems. The PET is added with a power electronic conversion circuit based on a high-frequency transformer, and the functions of the PET are realized by combining a power electronic device with the high-frequency transformer, and the PET has the functions of transformation, isolation and energy transmission due to the fact that the PET is provided with an alternating current interface and a direct current interface, so that the PET can be used as an electric energy router, and the coordination management of energy at a port is realized. An alternating current/direct current hybrid system constructed based on PET and other flexible equipment can improve the power grid structure and the access flexibility of renewable energy sources; the rapid regulation and control capability of the power grid for dealing with uncertainty is enhanced, and the coordination and complementation of the multiple types of renewable energy sources are realized; reducing the conversion links and improving the energy utilization efficiency.
At present, a series of optimization methods are provided for the optimal operation of an alternating current-direct current hybrid system by a team at home and abroad, however, the operation mode, network constraint and control object faced by the alternating current-direct current hybrid system are more complex, the optimal scheduling is influenced by a large amount of uncertainty, multidimensional optimization variables and operation constraint, and the optimization scheduling has obvious multi-time scale difference, so that the overall optimization operation difficulty of the system is increased, and the related problems are not yet completely solved. Although the application of the novel power electronic equipment provides a new regulation and control means for the full consumption and efficient utilization of renewable energy sources, a model for using the equipment for system-level optimal scheduling is still lacking, and the flexible regulation capability of the equipment cannot be fully utilized.
Disclosure of Invention
The invention aims to provide an optimal scheduling method of an alternating current-direct current hybrid system considering PET loss, which aims to solve the problem that the influence of power loss of a PET and energy storage equipment model in the operation process is not considered in the day-ahead optimal scheduling method of the alternating current-direct current hybrid system containing PET, realize the operation of novel power electronic equipment and the alternating current-direct current hybrid system to realize the flexible and efficient consumption of various renewable energy sources, and discuss the influence of PET efficiency on the optimal scheduling scheme of the system.
The invention solves the technical problems by adopting the following technical scheme:
an alternating current/direct current hybrid system optimization scheduling method considering PET loss is characterized by comprising the following steps:
s1, establishing an alternating current/direct current hybrid system model taking PET loss into account, wherein the alternating current/direct current hybrid system model comprises a PET optimization model taking the loss into account, a micro gas turbine model, an energy storage battery model, a fan model and a photovoltaic model;
s2, setting system balance constraint by taking the minimum system running cost as a target, and optimally scheduling the alternating current-direct current hybrid system considering PET loss.
Further, in the PET model considering the loss, PET is used as an intermediate junction for energy transmission, certain power loss exists in the PET, and three-port PET is taken as an example, and physical quantity PET net input power P is introduced PETt Represented by formulas (1) - (2):
in the method, in the process of the invention,the net input power of PET at the time t is represented by the sum of the total power of PET input from the main network, the alternating current area and the direct current area at the time t; η is the power conversion coefficient of PET; />The interaction power of the main network area and PET at the time t is represented;representing the interaction power of the alternating current region and PET at the time t; />The interaction power of the direct current region and PET at the time t is represented;
the optimized model for PET is represented by formula (3):
further, to ensure that the PET is operating in a safe state, the upper power limit constraint for the interaction power of its three ports is expressed as equations (4) - (6):
wherein P is M Maximum interaction power of PET and main network, P AC Maximum interaction power for PET and alternating current region, P DC Maximum interaction power for PET and dc region.
Further, in the micro gas turbine model, the output power of the micro gas turbine is taken as a control variable of the model, and the generated energy constraint is represented by formulas (7) - (9):
in the method, in the process of the invention,for the output of the micro gas turbine at time t, < >>For the output of the micro gas turbine at time t+1,/>For the upper limit value of the output power of the micro gas turbine, RU MT Is the upper limit of the output power rising rate of the micro gas turbine, RD MT Is the upper limit of the output power decline rate of the micro gas turbine.
Further, in the energy storage battery model, the operation loss of the energy storage battery is considered, and the charging upper limit value and the discharging upper limit value exist in each moment of charging and discharging of the energy storage system; in addition, the energy storage energy of the energy storage system at the final moment is the same as the energy storage energy at the initial moment; the operational constraints are expressed by formulas (10) - (12):
in the method, in the process of the invention,for the energy storage of the energy storage system at time t, < >>The energy is stored in the energy storage system at the time t-1; />The charge and discharge quantity of the energy storage system at the time t is calculated; sigma is the self-discharge coefficient; p (P) Dmax Upper limit value of discharge per unit time of energy storage system, P Cmax The charging upper limit value of the energy storage system at unit moment; />For the energy storage of the energy storage system at the initial moment, < >>And the energy is stored in the energy storage system at the final moment.
Further, in the fan model, the set wind speed satisfies Weibull distribution, and the probability density function and mathematical expectation can be expressed as formulas (13) - (14):
wherein f (·) is a probability density function; v wind Is wind speed sampling value (unit: m/s); k is a shape parameter; c is a scale parameter, E (·) is a mathematical expectation, Γ (·) is a Gamma function;
the output power of the blower is expressed as formula (15):
wherein P is WT The output power of the fan is; v in ,v r And v out The wind speed is the cut-in wind speed of the fan, and the rated wind speed and the cut-out wind speed (unit: m/s); p (P) wt Is the rated power of the fan.
Further, in the photovoltaic model, the photovoltaic output power is set to meet Beta distribution, and the probability density function and mathematical expectation are expressed as formulas (16) - (17):
wherein P is PV And (3) withThe actual output power and the maximum output power of the photovoltaic equipment; Γ (·) is a Gamma function; alpha and Beta are scale parameters of the Beta distribution. Will->Regarded as a per unit sampling variable, the value range is 0,1]The power output of the photovoltaic system is calculated by multiplying the variable by +.>
Further, considering the operating cost equipment maintenance costs, the micro gas turbine power generation costs, the energy storage loss costs, expressed as formulas (18) - (21):
wherein N is the total period number of one operation period, m WT 、m PV Maintenance cost coefficients for fans and photovoltaic equipment respectively,respectively generating power of a fan and photovoltaic at the moment t; m is m MT Generating cost coefficients for the micro gas turbine; c (C) buy Representing total electricity purchase cost, C sell Representing the total electricity selling cost, C buy Positive value, C sell Negative value, & lt>For the main network purchase electricity coefficient at the time t, < ->The electricity selling coefficient of the main network at the time t; m is m B Is the loss cost coefficient of energy storage;
with minimum running cost of the system, the objective function for establishing the AC/DC hybrid optimization schedule is expressed as a formula (22):
further, the power balance constraint of the system is expressed as equation (23):
in the method, in the process of the invention,for the moment t, system load is exchanged,/->And the load of the direct current system at the moment t.
The invention has the advantages and positive effects that:
1. the method can provide reference for the optimal scheduling of the alternating current-direct current hybrid system considering the PET loss, analyzes the influence of the PET and the energy storage equipment model on the power loss in the operation process, and has important significance for researching the influence of the PET electric energy conversion efficiency on the optimal scheduling of the alternating current-direct current hybrid system.
2. The calculation results of the invention show that the change of PET efficiency can possibly lead to the change of the running state of the AC/DC system at a certain moment, but the influence on the running state of the system is limited in general. In addition, the running cost of the system decreases as the efficiency of the PET increases.
Drawings
FIG. 1 is a system topology of an embodiment of the present invention;
fig. 2 is a graph showing the output power of the PET dc port and ac port for 24 hours in accordance with an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Examples
The embodiment provides an alternating current-direct current hybrid system optimization scheduling method considering Power Electronic Transformer (PET) loss, which comprises the following steps:
step one, establishing an alternating current-direct current hybrid system model considering PET loss
For an ac/dc hybrid system with distributed energy sources, PET acts as a contact device for the hybrid system to the main network. A PET optimization model, a micro gas turbine model, an energy storage battery model, a fan model, a photovoltaic model, and a load model, which take into account the losses, are first described.
1) PET model with loss
PET is taken as an intermediate hub for energy transmission, certain power loss exists in the PET, three-port PET is taken as an example, and physical quantity PET net input power is introducedRepresented by formulas (1) - (2):
in the method, in the process of the invention,the net input power of PET at the time t is represented by the sum of the total power of PET input from the main network, the alternating current area and the direct current area at the time t; η is the power conversion coefficient of PET; />The interaction power of the main network area and PET at the time t is represented;representing the interaction power of the alternating current region and PET at the time t; />The power of interaction of the DC domain with PET at time t is shown.
The optimized model for PET is represented by formula (3):
to ensure that the PET is operating in a safe state, the upper power limit constraint for the interaction power of its three ports is expressed as formulas (4) - (6):
wherein P is M Maximum interaction power of PET and main network, P AC Maximum interaction power for PET and alternating current region, P DC Maximum interaction power for PET and dc region.
2) Miniature gas turbine model
The output power of the micro gas turbine is taken as a control variable of a model, and the generated energy constraint is represented by formulas (7) - (9):
wherein P is MTt For the output of the micro gas turbine at time t,for the output of the micro gas turbine at time t+1,/>For the upper limit value of the output power of the micro gas turbine, RU MT Is the upper limit of the output power rising rate of the micro gas turbine, RD MT Is the upper limit of the output power decline rate of the micro gas turbine.
3) Energy storage battery model
Considering the running loss of the energy storage battery, wherein the charging upper limit value and the discharging upper limit value exist in each moment of charging and discharging of the energy storage system; in addition, the energy storage energy of the energy storage system at the final moment is the same as the energy storage energy at the initial moment. The operational constraints are expressed by formulas (10) - (12):
in the method, in the process of the invention,for the energy storage of the energy storage system at time t, < >>The energy is stored in the energy storage system at the time t-1; />The charge and discharge quantity of the energy storage system at the time t is calculated; sigma is the self-discharge coefficient; p (P) Dmax Upper limit value of discharge per unit time of energy storage system, P Cmax The charging upper limit value of the energy storage system at unit moment; />For the energy storage of the energy storage system at the initial moment, < >>And the energy is stored in the energy storage system at the final moment.
4) Fan model
The set wind speed satisfies the Weibull distribution, and the probability density function and mathematical expectation can be expressed as formulas (13) - (14):
wherein f (·) is a probability density function; v wind Is wind speed sampling value (unit: m/s); k is a shape parameter; c is the scale parameter, E (-) is the mathematical expectation, Γ (-) is the Gamma function.
The output power of the blower is expressed as formula (15):
wherein P is WT The output power of the fan is; v in ,v r And v out The wind speed is the cut-in wind speed of the fan, and the rated wind speed and the cut-out wind speed (unit: m/s); p (P) wt Is the rated power of the fan.
5) Photovoltaic model
The photovoltaic output power is set to satisfy the Beta distribution, and the probability density function and mathematical expectation are expressed as formulas (16) - (17):
wherein P is PV And (3) withThe actual output power and the maximum output power of the photovoltaic equipment; Γ (·) is a Gamma function; alpha and Beta are scale parameters of the Beta distribution. Will->Regarded as a per unit sampling variable, the value range is 0,1]The power output of the photovoltaic system is calculated by multiplying the variable by +.>
Step two, the objective function and constraint conditions of the optimization model are written in rows
Considering the operating cost and equipment maintenance costs, the micro gas turbine power generation costs, the energy storage loss costs, expressed as formulas (18) - (21):
wherein N is the total period number of one operation period, m WT 、m PV Maintenance cost coefficients for fans and photovoltaic equipment respectively,respectively generating power of a fan and photovoltaic at the moment t; m is m MT Generating cost coefficients for the micro gas turbine; c (C) buy Representing total electricity purchase cost, C sell Representing the total electricity selling cost, C buy Positive value, C sell Negative value, & lt>For the main network purchase electricity coefficient at the time t, < ->The electricity selling coefficient of the main network at the time t; m is m B Is a loss cost coefficient of energy storage.
With minimum running cost of the system, the objective function for establishing the AC/DC hybrid optimization schedule is expressed as a formula (22):
the power balance constraint of the system is expressed as equation (23):
in the method, in the process of the invention,for the moment t, system load is exchanged,/->For the load of the direct current system at the moment t, the meaning of other parameters is referred to the corresponding parameter description.
Application example
Taking a practical PET-containing alternating current-direct current hybrid system in Jiangsu province as an example, the topology structure of the system is shown in figure 1, the system consists of an alternating current network and a direct current network, the alternating current network and the direct current network transmit energy by means of PET, and three ports of the PET are connected with the alternating current network and the direct current network, and one port of the PET is directly connected with a main network. When the energy supply in the AC/DC system is insufficient or the economy of purchasing electricity from the main network is better, the system can purchase electricity from the main network and inject the electricity into the AC/DC system through PET so as to ensure the balance of energy supply and demand.
The alternating current system comprises a micro gas turbine (MT), a fan (WT), an alternating current controllable load (Controllable AC Loads, AC Lctrl) and an alternating current uncontrollable load (Non-Controllable AC loads, AC Lcri), wherein the generated energy of the micro gas turbine and the reduction amount of the alternating current controllable load at each moment are controlled variables, and the output of the fan and the load amount of the alternating current uncontrollable load are given values.
The direct current system comprises a photovoltaic power generation unit (PV), a battery energy storage device (BS), a direct current controllable load (Controllable DC Loads, DC Lctrl) and a direct current uncontrollable load (Non-Controllable DC loads, DC Lcri). The method comprises the steps of taking the reduction amount of the energy storage device, the photovoltaic power generation amount and the direct current controllable load at each moment as control variables, and taking the load amounts of the photovoltaic power output and the direct current uncontrollable load as given values. For the state of the battery, it is determined by the optimal solution whether it is charged or discharged at each instant. The battery can be considered as a load when charged; when it is discharged, it can be regarded as a power generation device.
The present calculation example performs optimization scheduling on the system in the day before, takes the optimization scheduling step length as 1h, ignores the self-discharge coefficient of the energy storage battery, and the equipment configuration parameters and the cost coefficients of all parts of the system are shown in table 1.
TABLE 1 AC/DC mixing system parameters for actual PET in Jiangsu province
The output power of the PET dc port and ac port is given in fig. 2 for 24 hours, with positive values indicating that power is flowing from the ac/dc system and negative values indicating that power is being injected into the ac/dc system. Table 2 shows the state values and the operating states of the three parts of the ac system, the dc system and the main network to which the PET was connected within 24 hours.
Table 2 state values of PET three ports (η=0.95)
In the discussion of the influence of PET efficiency on the optimal scheduling, the system is optimized and scheduled in advance by taking eta=0.92, 0.95 and 0.98 respectively, the state values of three parts of an alternating current system, a direct current system and a main network connected with PET within 24 hours when eta=0.95 are given in the table 2 in the upper section, and the state values of three parts of the alternating current system, the direct current system and the main network when eta=0.92 and 0.98 are given in the table 3 and the table 4 in the lower section respectively.
Table 3 state values of PET three ports (η=0.92)
Table 4 state values of PET three ports (η=0.98)
/>
TABLE 5 cost of system operation at different PET efficiencies
Comparing Table 3 with Table 2, the state values of the AC system and the DC system are changed only in the AC state at 15 hours and the DC state at 16 hours; comparing table 4 with table 2, the AC state at 15 hours only changed for the state values of the AC system and the dc system. Analysis of the data shows that the AC and DC surplus data also float due to the variation in PET efficiency, resulting in the possibility of variation in the value that is originally in the critical state after fluctuation.
The total operating costs for the system at the three operating efficiencies are given in table 5, which shows that the total operating costs for the PET-containing system decrease with increasing PET efficiency.
The invention provides an alternating current/direct current hybrid system optimization scheduling method considering the loss of a Power Electronic Transformer (PET), which analyzes the influence of PET operation efficiency on system operation scheduling. The calculation result shows that:
1) Changes in PET efficiency may result in changes in the operating state of the ac-dc system at a certain time, but generally have limited impact on the system operating state.
2) The running cost of the system decreases as the efficiency of the PET increases.
The method for optimizing and dispatching the PET-containing alternating current-direct current hybrid micro-grid is studied more deeply and is a direction to be studied deeply in the future.
Although the embodiments of the present invention and the accompanying drawings have been disclosed for illustrative purposes, those skilled in the art will appreciate that: various substitutions, changes and modifications are possible without departing from the spirit and scope of the invention and the appended claims, and therefore the scope of the invention is not limited to the embodiments and the disclosure of the drawings.
Claims (8)
1. An alternating current/direct current hybrid system optimization scheduling method considering PET loss is characterized by comprising the following steps:
s1, establishing an alternating current/direct current hybrid system model taking PET loss into account, wherein the model comprises a PET optimization model taking loss into account, a miniature gas turbine model, an energy storage battery model, a fan model, a photovoltaic model and a load model;
s2, setting system balance constraint by taking the minimum system running cost as a target, and optimally scheduling an alternating current-direct current hybrid system considering PET loss;
in the PET optimization model for accounting for the loss, PET is used as an intermediate junction for energy transmission, certain power loss exists in the PET, three-port PET is taken as an example, and physical quantity PET net input power is introducedRepresented by formulas (1) - (2):
in the method, in the process of the invention,the net input power of PET at the time t is represented by the sum of the total power of PET input from the main network, the alternating current area and the direct current area at the time t; η is the power conversion coefficient of PET; />The interaction power of the main network area and PET at the time t is represented; />Representing the interaction power of the alternating current region and PET at the time t; />The interaction power of the direct current region and PET at the time t is represented;
the optimized model for PET is represented by formula (3):
2. the optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: to ensure that the PET is operating in a safe state, the upper power limit constraint for the interaction power of its three ports is expressed as formulas (4) - (6):
wherein P is M Maximum interaction power of PET and main network, P AC Maximum interaction power for PET and alternating current region, P DC Maximum interaction power for PET and dc region.
3. The optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the micro gas turbine model, the output power of the micro gas turbine is taken as a control variable of the model, and the generated energy constraint is represented by formulas (7) - (9):
in the method, in the process of the invention,for the output of the micro gas turbine at time t, < >>For the output of the micro gas turbine at time t+1,/>For the upper limit value of the output power of the micro gas turbine, RU MT Is the upper limit of the output power rising rate of the micro gas turbine, RD MT Is the upper limit of the output power decline rate of the micro gas turbine.
4. The optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the energy storage battery model, the running loss of the energy storage battery is considered, and the charging upper limit value and the discharging upper limit value exist in each moment of charging and discharging of the energy storage system; in addition, the energy storage energy of the energy storage system at the final moment is the same as the energy storage energy at the initial moment; the operational constraints are expressed by formulas (10) - (12):
in the method, in the process of the invention,for the energy storage of the energy storage system at time t, < >>The energy is stored in the energy storage system at the time t-1; />The charge and discharge quantity of the energy storage system at the time t is calculated; sigma is the self-discharge coefficient; p (P) Dmax Upper limit value of discharge per unit time of energy storage system, P Cmax The charging upper limit value of the energy storage system at unit moment; />For the energy storage of the energy storage system at the initial moment, < >>And the energy is stored in the energy storage system at the final moment.
5. The optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the fan model, the set wind speed meets Weibull distribution, and the probability density function and mathematical expectation can be expressed as formulas (13) - (14):
wherein f (·) is a probability density function; v wind Is wind speed sampling value (unit: m/s); k is a shape parameter; c is a scale parameter, E (·) is a mathematical expectation, Γ (·) is a Gamma function;
the output power of the blower is expressed as formula (15):
wherein P is WT The output power of the fan is; v in ,v r And v out The wind speed is the cut-in wind speed of the fan, and the rated wind speed and the cut-out wind speed (unit: m/s); p (P) wt Is the rated power of the fan.
6. The optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: in the photovoltaic model, the photovoltaic output power is set to meet Beta distribution, and probability density functions and mathematical expectations of the photovoltaic output power are expressed as formulas (16) - (17):
wherein P is PV And (3) withThe actual output power and the maximum output power of the photovoltaic equipment; Γ (·) is a Gamma function; alpha and Beta are scale parameters of Beta distribution; will->Regarded as a per unit sampling variable, the value range is 0,1]The power output of the photovoltaic system is calculated by multiplying the variable by +.>
7. The optimal scheduling method for the alternating current-direct current hybrid system considering PET loss according to claim 1, wherein the optimal scheduling method is characterized by comprising the following steps of: considering the operating cost and equipment maintenance costs, the micro gas turbine power generation costs, the energy storage loss costs, expressed as formulas (18) - (21):
wherein N is the total period number of one operation period, m WT 、m PV Maintenance cost coefficients for fans and photovoltaic equipment respectively,respectively generating power of a fan and photovoltaic at the moment t; m is m MT Generating cost coefficients for the micro gas turbine; c (C) buy Representing total electricity purchase cost, C sell Representing the total electricity selling cost, C buy Positive value, C sell Negative value, & lt>For the main network purchase electricity coefficient at the time t, < ->The electricity selling coefficient of the main network at the time t; m is m B Is the loss cost coefficient of energy storage;
with minimum running cost of the system, the objective function for establishing the AC/DC hybrid optimization schedule is expressed as a formula (22):
8. the optimal scheduling method for the alternating current-direct current hybrid system considering PET losses according to claim 7, wherein the power balance constraint of the system is expressed as formula (23):
in the method, in the process of the invention,for the moment t, system load is exchanged,/->And the load of the direct current system at the moment t.
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