CN113313295A - Comprehensive station optimized operation method in multi-station fusion mode - Google Patents
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Abstract
A method for optimizing operation of a comprehensive station in a multi-station fusion mode comprises the following steps: collecting operation data of a comprehensive station in a multi-station fusion mode; establishing constraint conditions of the state of charge, the charge and discharge power and the power balance of the energy storage power station; the constraint conditions of the charge state and the charge and discharge power meet the constraint of the installation capacity of the energy storage power station; calculating power supply load, investment cost, operation cost and electricity purchasing cost of each power grid; and constructing a total cost function model, and solving to obtain a charge-discharge power optimization result of the energy storage power station and a load power optimization result participating in response by using the minimum running total cost as a target function and utilizing various constraint conditions. The method aims at minimizing the total cost, reduces the energy storage configuration capacity under the condition of meeting the load requirement of a data center, saves the construction cost of a power grid, saves the power utilization cost by utilizing the time-of-use electricity price, provides theoretical basis and technical support for the urban multi-station fusion construction operation, and ensures the economy, environmental protection and reliability of the construction operation of the power station.
Description
Technical Field
The invention relates to the technical field of operation control of power systems, in particular to an optimization operation method of a comprehensive station in a multi-station fusion mode.
Background
With the development of the energy industry in China, the energy development is unbalanced and insufficient, the requirement on green low-carbon energy is increased, and a clean low-carbon, safe and efficient energy system is urgently needed to be constructed. The ubiquitous power internet of things serves as an important construction target, and meanwhile, the urban informatization aspect is oriented to innovation services. The multi-station integration is used as important application of ubiquitous power internet of things, resources such as an energy storage power station, a data center station, a photovoltaic power station and a transformer substation are integrated, resource allocation of a city is optimized, the data sensing and analysis and operation capacity of equipment is improved, and energy consumption is promoted. With the increase of the requirements of customers on the quality and the stability of electric energy, the value-added task of multi-station integration operation is further developed.
In the prior art, multi-station fusion is an important landing content of new infrastructure, and the multi-station fusion is that on the basis of existing transformer substation resources, transformer substation resources are fully utilized, functional stations such as a data center station, an energy storage station, a charging (converting) power station and a photovoltaic power station are built, power grid service data are comprehensively borne, increasing data storage, integration and value-added operation requirements are met, three-in-one of energy source flow, service flow and data flow is realized, intelligent power grid services which are firmly supported in the interior are cultivated in the ubiquitous power internet of things market, and shared enterprise construction is promoted. However, the current research content on the multi-station integration mainly focuses on the field of "energy storage power station + charging station", and the research on the field of "photovoltaic power station + energy storage power station + data center + charging station" is still blank, and especially the research on the comprehensive station optimization operation method in the multi-station integration mode is urgently needed.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a comprehensive station optimized operation method in a multi-station fusion mode, which combines energy storage control and charging station control by considering response time-of-use electricity price, compensates load power responding according to the time-of-use electricity price by using energy storage, and performs peak clipping and valley filling on power grid load by considering the cost and the income of an energy storage power station, thereby not only meeting the load requirements of users, but also reducing the peak-valley difference of the power grid load.
The invention adopts the following technical scheme.
A method for optimizing operation of a comprehensive station in a multi-station fusion mode comprises the following steps:
step 1, collecting operation data of a comprehensive station in a multi-station fusion mode;
step 2, establishing a charge state constraint condition, a charge and discharge power constraint condition and a power balance constraint condition of the energy storage power station; the constraint relation based on the installation capacity of the energy storage power station is met between the charge state constraint condition and the charge and discharge power constraint condition;
step 3, calculating power supply load, investment cost, operation cost and electricity purchasing cost of the power grid according to the operation data;
step 4, constructing a total cost function model according to the calculation result of the step 3, and establishing an optimized operation model by taking the minimum operation total cost as a target function;
and 5, solving the optimized operation model by using the constraint conditions in the step 2 to obtain a charge and discharge power optimization result of the energy storage power station and a load power optimization result participating in response.
Preferably, in step 1, the operation data includes: electricity price, data center load, electric vehicle charging station load, and design service life of the power station.
Preferably, in step 2, the state of charge constraint condition satisfies the following relation:
SOCmin≤SOCt≤SOCmax
in the formula (I), the compound is shown in the specification,
SOCtis the state of charge of the battery at time t,
SOCminis the minimum state of charge of the battery,
SOCmaxis the maximum state of charge of the battery;
the charge and discharge power constraint condition satisfies the following relational expression:
in the formula (I), the compound is shown in the specification,
αc，tis the battery state of charge ratio at time t,
αd，tis the battery discharge state ratio at time t,
Pcfor the charging power of the battery to be charged,
Pdis the discharge power of the battery and is,
Pc，maxis the maximum charging power of the battery,
Pd，maxis the maximum discharge power of the battery.
Preferably, in the energy storage power station, for any time t, a constraint relation based on the capacity of the energy storage power station is satisfied between the state of charge constraint condition and the charge-discharge power constraint condition, and the following relation is satisfied:
SOCt-1·C+ηcPcΔt-Pd/ηdΔt≤C
in the formula (I), the compound is shown in the specification,
SOCt-1is the state of charge of the battery at time t-1,
c is the installation capacity of the energy storage power station,
ηcin order to achieve the charging efficiency of the battery,
ηdin order to achieve the discharge efficiency of the battery,
Δ t is the time step.
Preferably, in step 2, the energy sources required by daily operation of the comprehensive station under the multi-station fusion model include: the electric energy is purchased to the electric wire netting, the generated energy of the storage energy of energy storage power station, photovoltaic power station, and energy consumption includes: the power balance constraint conditions of the power consumption power of the data center, the power consumption power of the electric vehicle charging station and the charging power of the energy storage power station satisfy the following relational expression:
Ps，t+Pc，t+Pcd，t＝Pg，t+Pd，t+Pl，t
in the formula (I), the compound is shown in the specification,
Ps，tfor the time t the data centre consumes power,
Pcd，tthe electric power consumed by the electric vehicle charging station at the moment t,
Pc，tfor the charging power of the energy storage power station at time t,
Pg，tthe power is purchased for the power grid at the time t,
Pd，tthe discharge power of the energy storage power station at the moment t is used for representing the stored energy of the energy storage power station,
Pl，tthe generated energy of the photovoltaic power station at the moment t.
Preferably, step 3 comprises:
step 3.1, taking one day as a unit, extracting all load data from the operation data, and performing accumulation calculation on all load data to obtain a power supply load of the power grid;
and 3.2, the investment cost meets the following relational expression:
Fi＝Fi，c+Fi，l+Fi，d
in the formula (I), the compound is shown in the specification,
Fiin order to achieve the purpose of investment cost,
Fi，cin order to save the investment cost of the energy storage power station,
Fi，lin order to reduce the investment cost of the photovoltaic power station,
Fi，dinvestment cost for electric vehicle charging stations;
step 3.3, the operation cost meets the following relational expression:
Fm＝Fm，s+Fm，c+Fm，l
in the formula (I), the compound is shown in the specification,
Fmin order to account for the overall maintenance costs,
Fm，sin order to increase the operating costs of the data center equipment,
Fm，cin order to reduce the operating costs of an electric vehicle charging station,
Fm，lthe operating cost of the photovoltaic power station;
step 3.4, the purchase-declaration cost meets the following relational expression:
in the formula (I), the compound is shown in the specification,
Fgin order to achieve the cost of electricity purchase,
Pg，tthe power is purchased for the power grid at the time t,
ptfor a unit price of electricity purchased from the grid at time t,
Δ t is the time step.
Preferably, in step 3.2, considering the depreciation rate of the storage battery, the investment cost of the energy storage power station is the average daily cost of the primary charge of the storage battery in the recycling years, and the following relation is satisfied:
in the formula (I), the compound is shown in the specification,
fifor the investment cost of unit capacity of the energy storage power station,
c is the installation capacity of the energy storage power station,
f is the investment cost factor.
Preferably, in step 3.2, the investment cost of the photovoltaic power station includes the investment and construction cost of the panel, the investment and construction cost of the photovoltaic inverter, the investment and construction cost of the ac/dc cable, and the investment and construction cost of the power distribution cabinet, and the investment cost of the photovoltaic power station is the average cost to each day of the once investment cost of the photovoltaic power station within the recovery period, and satisfies the following relational expression:
in the formula (I), the compound is shown in the specification,
fcoin order to obtain the coefficient of recovery of the photovoltaic power station,
Cwpin order to be able to install the photovoltaic system,
fevthe average investment cost per kilowatt of the photovoltaic power station.
Preferably, in step 3.2, considering the depreciation rate of the charging pile, the investment cost of the electric vehicle charging station is the average daily cost of the charging station per charge within the recycling year, and the following relation is satisfied:
in the formula (I), the compound is shown in the specification,
Pithe investment cost per unit capacity of the electric vehicle charging station,
Ccdin order to provide the installation capacity of the electric vehicle,
f is an investment cost factor.
In step 4, an optimized operation model of the comprehensive station is established by taking the minimum total operation cost as an objective function, and the following relational expression is satisfied:
min F＝Fi+Fm+Fg
in the formula (I), the compound is shown in the specification,
min F is the minimum total cost of operation,
Fiis the cost of the investment, and the cost of the investment,
Fmis the cost of the operation of the process,
Fgis the cost of electricity purchase.
Compared with the prior art, the method has the advantages that the load power of the time-of-use electricity price is compensated and responded by the energy storage on the premise of ensuring the service quality of the data center, the total cost of the optimized operation of the comprehensive station is minimized, peak clipping and valley filling can be realized, the load peak-valley difference of the power grid is reduced, the configuration capacity of the energy storage is reduced on the premise of meeting the load requirements of users, the electricity utilization cost of the users and the construction cost of the power grid are saved, and the utilization efficiency of power system equipment is improved. When the energy storage power station operates, the energy storage battery stores electric quantity for standby, power failure is prevented, the stability and the reliability of system operation are improved, and the new energy consumption level can be improved by the access of the roof photovoltaic power station. Meanwhile, theoretical basis and technical support are provided for urban multi-station fusion construction and operation, and the economical efficiency, environmental protection and reliability of power station construction and operation are guaranteed.
Drawings
Fig. 1 is a schematic flow chart of a method for optimizing operation of an integrated station in a multi-station fusion mode according to the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 1, a method for optimizing operation of a comprehensive station in a multi-station fusion mode includes:
step 1, collecting operation data of a comprehensive station in a multi-station fusion mode.
Specifically, in step 1, the operation data includes: electricity price, data center load, electric vehicle charging station load, and design service life of the power station.
Step 2, establishing a charge state constraint condition, a charge and discharge power constraint condition and a power balance constraint condition of the energy storage power station; and the constraint relation based on the installation capacity of the energy storage power station is met between the charge state constraint condition and the charge and discharge power constraint condition.
Specifically, in step 2, the state of charge constraint condition satisfies the following relation:
SOCmin≤SOCt≤SOCmax
in the formula (I), the compound is shown in the specification,
SOCtis the state of charge of the battery at time t,
SOCminis the minimum state of charge of the battery,
SOCmaxis the maximum state of charge of the battery;
the charge and discharge power constraint condition satisfies the following relational expression:
in the formula (I), the compound is shown in the specification,
αc，tis the battery state of charge ratio at time t,
αd，tis the battery discharge state ratio at time t,
Pcfor the charging power of the battery to be charged,
Pdis the discharge power of the battery and is,
Pc，maxis the maximum charging power of the battery,
Pd，maxis the maximum discharge power of the battery.
In the energy storage power station, for any time t, a constraint relation based on the capacity of the energy storage power station is satisfied between a charge state constraint condition and a charge and discharge power constraint condition, and the following steps are shown:
SOCt-1·C+ηcPcΔt-Pd/ηdΔt≤C
in the formula (I), the compound is shown in the specification,
SOCt-1is the state of charge of the battery at time t-1,
c is the installation capacity of the energy storage power station,
ηcin order to achieve the charging efficiency of the battery,
ηdin order to achieve the discharge efficiency of the battery,
Δ t is the time step, which in the preferred embodiment takes 1 hour.
Specifically, in step 2, the energy sources required by daily operation of the comprehensive station under the multi-station fusion model include: the electric energy is purchased to the electric wire netting, the generated energy of the storage energy of energy storage power station, photovoltaic power station, and energy consumption includes: the power balance constraint conditions of the power consumption power of the data center, the power consumption power of the electric vehicle charging station and the charging power of the energy storage power station satisfy the following relational expression:
Ps，t+Pc，t+Pcd，t＝Pg，t+Pd，t+Pl，t
in the formula (I), the compound is shown in the specification,
Ps，tfor the time t the data centre consumes power,
Pcd，tthe electric power consumed by the electric vehicle charging station at the moment t,
Pc，tfor the charging power of the energy storage power station at time t,
Pg，tthe power is purchased for the power grid at the time t,
Pd，tthe discharge power of the energy storage power station at the moment t is used for representing the stored energy of the energy storage power station,
Pl，tthe generated energy of the photovoltaic power station at the moment t.
And 3, calculating the power supply load, the investment cost, the operation cost and the electricity purchasing cost of the power grid according to the operation data.
Step 3.1, taking one day as a unit, extracting all load data from the operation data, and performing accumulation calculation on all load data to obtain a power supply load of the power grid;
and 3.2, the investment cost meets the following relational expression:
Fi＝Fi，c+Fi，l+Fi，d
in the formula (I), the compound is shown in the specification,
Fiin order to achieve the purpose of investment cost,
Fi，cin order to save the investment cost of the energy storage power station,
Fi，lin order to reduce the investment cost of the photovoltaic power station,
Fi，dinvestment cost for electric vehicle charging stations;
specifically, in step 3.2, considering the depreciation rate of the storage battery, the investment cost of the energy storage power station is the average daily cost of the primary charge of the storage battery in the recovery period, and the following relational expression is satisfied:
in the formula (I), the compound is shown in the specification,
fifor the investment cost of unit capacity of the energy storage power station,
c is the installation capacity of the energy storage power station,
f is the investment cost factor.
Specifically, in step 3.2, the investment cost of the photovoltaic power station includes the investment and construction cost of the panel, the investment and construction cost of the photovoltaic inverter, the investment and construction cost of the alternating current/direct current cable and the investment and construction cost of the power distribution cabinet, the investment cost of the photovoltaic power station is the average cost to each day within the recovery year of the photovoltaic power station, and the following relational expression is satisfied:
in the formula (I), the compound is shown in the specification,
fcoin order to obtain the coefficient of recovery of the photovoltaic power station,
Cwpin order to be able to install the photovoltaic system,
fevthe average investment cost per kilowatt of the photovoltaic power station.
Wherein the recovery factor f of the photovoltaic power stationcoSatisfies the following relation:
in the formula, r is the current rate, i.e. the ratio of the predicted value to the current value of the photovoltaic system, and n is the depreciation age of the photovoltaic system.
Specifically, in step 3.2, considering the depreciation rate of the charging pile, the investment cost of the electric vehicle charging station is the average daily cost of the charging station per charge within the recovery period, and the following relation is satisfied:
in the formula (I), the compound is shown in the specification,
Pithe investment cost per unit capacity of the electric vehicle charging station,
Ccdin order to provide the installation capacity of the electric vehicle,
f is an investment cost factor.
In the preferred embodiment, the operation cost of each station after the power supply load and the time-of-use electricity price of the power grid is calculated based on the constraint conditions established in the step 2 and the original data collected in the step 1; and the capacity of the energy storage system is optimally configured, and the energy storage participates in peak clipping and valley filling operation on the premise of reserving the standby power of the data center.
At the time of 0:00-7:00, the electricity purchasing price is lower, the storage battery of the energy storage system is charged, and the storage battery is in a full state at the time of 7: 00; the electricity purchase price at the time of 8:00-11:00 is higher, and in order to reduce the operation cost, the storage battery discharges electricity; the time 11:00-23:00 is the ordinary time and the peak time of the electricity purchasing price, and in order to reduce the electricity purchasing quantity at the peak time, the battery of the energy storage power station is charged at the time 11:00-18:00 when the electricity purchasing price is lower; at 18:00-23:00, the battery discharges.
Step 3.3, the operation cost meets the following relational expression:
Fm＝Fm，s+Fm，c+Fm，l
in the formula (I), the compound is shown in the specification,
Fmin order to account for the overall maintenance costs,
Fm，sin order to increase the operating costs of the data center equipment,
Fm，cis powered electricallyThe cost of operating a vehicle charging station,
Fm，lthe operating cost of the photovoltaic power station;
further, the equipment operation cost of the data center satisfies the following relational expression:
in the formula, Ps，tIs the power of the server at time t, pmIs the cost per unit power of the equipment of the data center.
Further, in the operation process of the electric vehicle charging station, safety monitoring and maintenance of the system are required. The operation cost of the electric vehicle charging station is in direct proportion to the electric quantity output by the system, and the following relational expression is satisfied:
in the formula, kmOperating factor, P, for electric vehicle charging stationsc，tAnd outputting the charging output power of the electric vehicle charging station at the moment t.
Further, in the operation process of the photovoltaic power station, safety monitoring and maintenance are required to be carried out on the system. The maintenance cost of the photovoltaic power station is in direct proportion to the electric quantity output by the system, and the following relational expression is satisfied:
in the formula, kmFor the operational maintenance factor, P, of a photovoltaic power plantl，tAnd the photovoltaic output power of the photovoltaic power station at the moment t is obtained.
And 3.4, the electricity purchasing cost meets the following relational expression:
in the formula (I), the compound is shown in the specification,
Fgin order to achieve the cost of electricity purchase,
Pg，tthe power is purchased for the power grid at the time t,
ptfor a unit price of electricity purchased from the grid at time t,
Δ t is the time step, which in the preferred embodiment takes 1 hour.
Step 4, constructing a total cost function model according to the calculation result of the step 3, and establishing an optimized operation model by taking the minimum operation total cost as a target function;
specifically, in step 4, the minimum total running cost is taken as an objective function, and an optimized running model of the comprehensive station is established, and the following relational expression is satisfied:
min F＝Fi+Fm+Fg
in the formula (I), the compound is shown in the specification,
min F is the minimum total cost of operation,
Fiis the cost of the investment, and the cost of the investment,
Fmis the cost of the operation of the process,
Fgis the cost of electricity purchase.
And 5, solving the optimized operation model by using the constraint conditions in the step 2 to obtain a charge and discharge power optimization result of the energy storage power station and a load power optimization result participating in response.
Compared with the prior art, the method has the advantages that the load power of the time-of-use electricity price is compensated and responded by the energy storage on the premise of ensuring the service quality of the data center, the total cost of the optimized operation of the comprehensive station is minimized, peak clipping and valley filling can be realized, the load peak-valley difference of the power grid is reduced, the configuration capacity of the energy storage is reduced on the premise of meeting the load requirements of users, the electricity utilization cost of the users and the construction cost of the power grid are saved, and the utilization efficiency of power system equipment is improved. When the energy storage power station operates, the energy storage battery stores electric quantity for standby, power failure is prevented, the stability and the reliability of system operation are improved, and the new energy consumption level can be improved by the access of the roof photovoltaic power station. Meanwhile, theoretical basis and technical support are provided for urban multi-station fusion construction and operation, and the economical efficiency, environmental protection and reliability of power station construction and operation are guaranteed.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (10)
1. A method for optimizing operation of a comprehensive station in a multi-station fusion mode is characterized in that,
the method comprises the following steps:
step 1, collecting operation data of a comprehensive station in a multi-station fusion mode;
step 2, establishing a charge state constraint condition, a charge and discharge power constraint condition and a power balance constraint condition of the energy storage power station; the constraint relation based on the installation capacity of the energy storage power station is met between the charge state constraint condition and the charge and discharge power constraint condition;
step 3, calculating power supply load, investment cost, operation cost and electricity purchasing cost of the power grid according to the operation data;
step 4, constructing a total cost function model according to the calculation result of the step 3, and establishing an optimized operation model by taking the minimum operation total cost as a target function;
and 5, solving the optimized operation model by using the constraint conditions in the step 2 to obtain a charge and discharge power optimization result of the energy storage power station and a load power optimization result participating in response.
2. The method for optimized operation of an integrated station in multi-station converged mode according to claim 1,
in step 1, the operation data includes: electricity price, data center load, electric vehicle charging station load, and design service life of the power station.
3. The method for optimized operation of an integrated station in multi-station converged mode according to claim 1,
in the step 2, the state of charge constraint condition satisfies the following relational expression:
SOCmin≤SOCt≤SOCmax
in the formula, SOCtIs the state of charge, SOC, of the battery at time tminIs the minimum state of charge, SOC, of the batterymaxIs the maximum state of charge of the battery;
the charge and discharge power constraint condition satisfies the following relational expression:
in the formula, alphac，tIs the battery state of charge ratio at time t, alphad，tIs the ratio of the discharge state of the battery at time t, PcFor charging power of the battery, PdIs the discharge power of the battery, Pc，maxIs the maximum charging power, P, of the batteryd，maxIs the maximum discharge power of the battery.
4. The method for optimized operation of an integrated station in multi-station converged mode according to claim 3,
in the energy storage power station, for any time t, a constraint relation based on the capacity of the energy storage power station is satisfied between the charge state constraint condition and the charge and discharge power constraint condition, and the following relation is satisfied:
SOCt-1·C+ηcPcΔt-Pd/ηdΔt≤C
in the formula, SOCt-1The state of charge of the battery at the moment t-1, C the installation capacity of the energy storage power station, etacIs the charging efficiency of the battery, etadΔ t is the time step for the discharge efficiency of the cell.
5. The method for optimized operation of an integrated station in multi-station converged mode according to claim 1,
in step 2, the energy sources required by daily operation of the comprehensive station under the multi-station fusion model comprise: the electric energy is purchased to the electric wire netting, the generated energy of the storage energy of energy storage power station, photovoltaic power station, and energy consumption includes: the power balance constraint condition comprises the following relational expression:
Ps，t+Pc，t+Pcd，t＝Pg，t+Pd，t+Pl，t
in the formula (I), the compound is shown in the specification,
Ps，tfor the time t the data centre consumes power,
Pcd，tthe electric power consumed by the electric vehicle charging station at the moment t,
Pc，tfor the charging power of the energy storage power station at time t,
Pg，tthe power is purchased for the power grid at the time t,
Pd，tthe discharge power of the energy storage power station at the moment t is used for representing the stored energy of the energy storage power station,
Pl，tthe generated energy of the photovoltaic power station at the moment t.
6. The method for optimized operation of an integrated station in multi-station converged mode according to claim 1,
the step 3 comprises the following steps:
step 3.1, taking one day as a unit, extracting all load data from the operation data, and performing accumulation calculation on all load data to obtain a power supply load of the power grid;
and 3.2, the investment cost meets the following relational expression:
Fi＝Fi，c+Fi，l+Fi，d
in the formula, FiFor investment costs, Fi，cFor investment costs of energy storage power stations, Fi，lFor investment costs of photovoltaic power stations, Fi，dInvestment cost for electric vehicle charging stations;
step 3.3, the operation cost meets the following relational expression:
Fm＝Fm，s+Fm，c+Fm，l
in the formula, FmFor total maintenance costs, Fm，sFor the operating costs of the data center equipment, Fm，cOperating costs for electric vehicle charging stations, Fm，lThe operating cost of the photovoltaic power station;
and 3.4, the electricity purchasing cost meets the following relational expression:
in the formula, FgFor purchase of electricity cost, Pg，tFor purchasing power, p, from the grid at time ttAnd delta t is the time step length of the unit electricity price of the electricity purchased from the power grid at the moment t.
7. The method for optimized operation of an integrated station in multi-station converged mode according to claim 6,
in the step 3.2, considering the depreciation rate of the storage battery, the investment cost of the energy storage power station is the average daily cost of the primary investment expense of the storage battery within the recovery period, and the following relational expression is satisfied:
in the formula (f)iThe unit capacity investment cost of the energy storage power station, the installation capacity of the energy storage power station and the investment cost factor f.
8. The method for optimized operation of an integrated station in multi-station converged mode according to claim 6,
in step 3.2, the investment cost of the photovoltaic power station comprises the investment and construction cost of the panel, the investment and construction cost of the photovoltaic inverter, the investment and construction cost of the alternating current/direct current cable and the investment and construction cost of the power distribution cabinet, the investment cost of the photovoltaic power station is the average cost to each day within the recycling years of the primary investment cost of the photovoltaic power station, and the following relational expression is satisfied:
in the formula (f)coIs the coefficient of recovery of the photovoltaic power plant, CwpIs the installation capacity of the photovoltaic system, fevThe average investment cost per kilowatt of the photovoltaic power station.
9. The method for optimized operation of an integrated station in multi-station converged mode according to claim 6,
in step 3.2, considering the depreciation rate of the charging pile, the investment cost of the electric vehicle charging station is the average daily cost of the charge station per charge within the recovery period, and the following relational expression is satisfied:
in the formula, PiInvestment cost per unit capacity for electric vehicle charging stations, CcdF is the installation capacity of the electric automobile and is the investment cost factor.
10. The method for optimized operation of an integrated station in multi-station converged mode according to claim 1,
in step 4, an optimized operation model of the comprehensive station is established by taking the minimum total operation cost as an objective function, and the following relational expression is satisfied:
min F＝Fi+Fm+Fg
where minF is the minimum total cost of operation, FiIs the investment cost, FmIs the running cost, FgIs the cost of electricity purchase.
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