CN111884253A - Wind-solar storage and charging campus micro-grid system and control method thereof - Google Patents

Wind-solar storage and charging campus micro-grid system and control method thereof Download PDF

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CN111884253A
CN111884253A CN202010737401.0A CN202010737401A CN111884253A CN 111884253 A CN111884253 A CN 111884253A CN 202010737401 A CN202010737401 A CN 202010737401A CN 111884253 A CN111884253 A CN 111884253A
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energy storage
storage unit
power
hybrid energy
grid
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CN111884253B (en
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彭坤
李俊芳
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Hunan Red Solar New Energy Science And Technology Co ltd
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Hunan Red Solar New Energy Science And Technology Co ltd
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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
    • 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
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
    • 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
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • 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
    • 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
    • H02J3/388—Islanding, i.e. disconnection of local power supply from the network
    • 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
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
    • H02J7/345—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering using capacitors as storage or buffering devices
    • 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
    • H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
    • H02J7/35—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
    • 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
    • H02J9/00—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting
    • H02J9/04—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source
    • H02J9/06—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over, e.g. UPS systems
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H02J2300/26—The renewable source being solar energy of photovoltaic origin involving maximum power point tracking control for photovoltaic sources
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • 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
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/40—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation wherein a plurality of decentralised, dispersed or local energy generation technologies are operated simultaneously
    • 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
    • H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/58—The condition being electrical
    • H02J2310/60—Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
    • 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
    • Y02B10/70—Hybrid systems, e.g. uninterruptible or back-up power supplies integrating renewable energies
    • 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
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • 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
    • Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02B90/20—Smart grids as enabling technology in buildings sector
    • 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
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers
    • 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
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • 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
    • 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
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles
    • Y02T90/167—Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/12—Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation
    • Y04S10/126—Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/12—Energy storage units, uninterruptible power supply [UPS] systems or standby or emergency generators, e.g. in the last power distribution stages
    • 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
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/248—UPS systems or standby or emergency generators
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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S30/00—Systems supporting specific end-user applications in the sector of transportation
    • Y04S30/10—Systems supporting the interoperability of electric or hybrid vehicles
    • Y04S30/14—Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing
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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
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    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Business, Economics & Management (AREA)
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  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
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Abstract

The invention discloses a wind-solar storage and charging campus micro-grid system which comprises a distributed power generation unit and a hybrid energy storage unit, wherein the distributed power generation unit is connected with the hybrid energy storage unit; the distributed power generation unit comprises a photovoltaic system and a wind generating set, and the hybrid energy storage unit comprises a super capacitor and a lithium battery pack. The invention also discloses a control method of the micro-grid system, which is used for controlling the wind-solar energy storage and charging campus micro-grid system to switch between a grid-connected mode and an off-grid mode and carrying out energy optimization management on the hybrid energy storage unit based on reinforcement learning. The invention has the advantages of improving the electricity economy, improving the safety and stability of electricity utilization, prolonging the service life of the lithium battery pack and the like.

Description

Wind-solar storage and charging campus micro-grid system and control method thereof
Technical Field
The invention relates to the technical field of campus micro-grids, in particular to a wind-solar storage and charging campus micro-grid system and a control method thereof.
Background
With the gradual depletion of energy sources and the increasingly serious environmental pollution, the research on energy-saving and emission-reducing technology is concerned. Relevant policies are set in China as early as the 'eleven-five' period, and the 'eleventh five-year planning outline of national economy and social development' provides a restrictive index that the total energy consumption of domestic production is reduced by about 20% and the total emission of main pollutants is reduced by 10% in the 'eleven-five' period. In a newly published report, the united nations environmental planning agency (UNEP) states that global carbon emissions need to be reduced by 2.7% each year in 2020 to 2030 years in order to achieve the target set by paris agreement 2015, i.e., the global temperature rise is controlled within 2 ℃ before industrialization by 2100. In recent years, the situation of energy and environmental problems in China is severe, and great challenges are provided for energy saving and emission reduction work. China has made great improvements on energy structures, such as propulsion of new energy automobiles, promotion of new energy engineering machinery, development of electric power systems and the like, and gradually replaces the traditional internal combustion engine system with the electric power system.
Solar energy and wind energy have obtained national vigorous popularization and application as natural energy and green energy, along with the high-speed development in new energy automobile field, the demand of filling electric pile is also bigger and bigger, and outdoor filling electric pile often need connect long cable and building electric power system to be connected, for the construction that fills electric pile has increased the degree of difficulty, if can make full use of photovoltaic energy and wind energy, then not only can the energy saving, and for outdoor construction that fills electric pile provides more degrees of freedom.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides a wind-solar storage and charging campus micro-grid system and a control method thereof, wherein the wind-solar storage and charging campus micro-grid system is capable of improving electricity economy and electricity safety and stability.
In order to solve the technical problems, the invention adopts the technical scheme that:
a campus micro-grid system for wind and light storage and charging comprises distributed power generation units and hybrid energy storage units, wherein the distributed power generation units are connected with the hybrid energy storage units; the distributed power generation unit comprises a photovoltaic system and a wind generating set, and the hybrid energy storage unit comprises a super capacitor and a lithium battery pack.
The invention also discloses a control method of the wind-solar storage and charging campus micro-grid system, which is used for controlling the wind-solar storage and charging campus micro-grid system to switch between a grid-connected mode and an off-grid mode, wherein in the grid-connected mode:
when the energy of the photovoltaic system and the wind generating set is sufficient, the energy is preferentially supplied to a local load for use, the residual energy is used for charging the hybrid energy storage unit, and if the energy still remains, the hybrid energy storage unit is transmitted to the grid;
when the energy of the photovoltaic system and the wind generating set is insufficient and the SOC of the hybrid energy storage unit is more than or equal to a set value A, the distributed power generation unit and the hybrid energy storage unit simultaneously supply power to the load; when the SOC of the hybrid energy storage unit is smaller than a set value A, the distributed generation unit and the power grid supply power for the load at the same time, and the power grid charges the energy storage system at the same time;
when the energy of the photovoltaic system and the wind generating set is not available, and when the SOC of the hybrid energy storage unit is more than or equal to a set value A, the hybrid energy storage unit supplies power to a load; and when the SOC of the hybrid energy storage unit is less than the set value A, the power grid supplies power to the load, and simultaneously charges the hybrid energy storage unit.
Preferably, in off-grid mode:
when the energy of the photovoltaic system and the wind generating set is sufficient, the energy is preferentially supplied to a load for use, the residual energy charges the hybrid energy storage unit, and if the energy still remains, the power output of the photovoltaic system and the wind generating set is limited;
when the energy of the photovoltaic system and the wind generating set is insufficient,
when the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the distributed power generation unit and the hybrid energy storage unit simultaneously supply power to the load;
when the SOC of the hybrid energy storage unit is less than a set value A, the power consumption of the controllable load is limited, and the power supply of the important load is reserved;
when the SOC of the hybrid energy storage unit is equal to a set value B, stopping power supply until the electric quantity of the hybrid energy storage unit is recovered to the set value, and recovering normal power supply;
when the photovoltaic system and the wind generating set are without energy,
when the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the hybrid energy storage unit supplies power to a load;
when the SOC of the hybrid energy storage unit is less than a set value A, the power consumption of the controllable load is limited, and the power supply of the important load is reserved;
and when the SOC of the hybrid energy storage unit is equal to the set value B, stopping power supply until the electric quantity of the hybrid energy storage unit is recovered to the set value, and recovering normal power supply.
Preferably, the power of the hybrid energy storage unit, SoC and SoV are used as state variables stThe current of the lithium battery pack is used as an action variable atThe total energy loss of the hybrid energy storage unit as a reward function rtAnd performing power optimization based on reinforcement learning.
Preferably, the power management method based on reinforcement learning specifically includes:
the value of state s is defined as follows, which can be considered as a discounted sum of rewards
Figure BDA0002605598830000021
Wherein γ ∈ [0,1]]Represents a discount factor, rt+1Represents the reward at time t + 1; when the value of state s is optimal, the value function is rewritten as:
Figure BDA0002605598830000022
wherein,
Figure BDA0002605598830000023
representing the probability of transition from state s to state s',
Figure BDA0002605598830000024
represents a reward for transitioning from state s to state s';
determining an optimal strategy according to:
Figure BDA0002605598830000025
the optimal Q value for the optimal state-action value is defined as follows:
Figure BDA0002605598830000026
the Q value remains updated according to the following rule:
Q(s,a)＝Q(s,a)+α(r(s,a)+γmaxa'Q(s',a')-Q(s,a))
wherein alpha is a decline factor of [0,1 ].
Preferably, where the power is modeled as a smooth markov chain, the power transition probability matrix may be calculated by nearest neighbor and maximum likelihood estimation as follows:
Figure BDA0002605598830000031
wherein M isi,jRepresents from
Figure BDA0002605598830000032
To
Figure BDA0002605598830000033
Number of transfers of, MiRepresents from
Figure BDA0002605598830000034
Total number of transfers.
Preferably for the state variable stDiscretizing, namely discretizing diffusion voltage and residual electric quantity SoC of the lithium battery pack into:
Figure BDA0002605598830000035
wherein, UD(k) Diffusion voltage at time k, soc (k) remaining capacity at time k, and QbIndicates the capacity, eta of the battery packbRepresenting the coulomb efficiency of the cell, Δ t the sampling interval, τbatRepresents a battery time constant;
the voltage state SoV of the super capacitor can be derived from the following equation:
SoV(k+1)＝SoV(k)-ic(k)Δt/Cu
wherein, CuIs the super capacitor capacity.
Preferably, when power supply optimization is performed, a series of optimal action variables a (k) are obtained with minimum cost, wherein the cost includes lithium battery pack energy loss, super capacitor energy loss and DC/DC conversion module energy loss, and is expressed as follows:
Figure BDA0002605598830000036
where N represents the number of movement cycles and L represents the instantaneous loss, including the battery energy loss Lb(k) Energy loss L of super capacitorc(k) And DC/DC converter loss Ldcdc(k) The loss function is expressed as follows:
Figure BDA0002605598830000037
wherein eta isdcdc(k) Representing the efficiency, P, of the DC/DC converterbat(k) For the output power of the lithium battery, z is a logical value, which is 1 when charging and 0 when discharging.
Compared with the prior art, the invention has the advantages that:
the micro-grid system can utilize the stored energy of the hybrid energy storage unit to carry out peak clipping and valley filling, can solve the problem of output fluctuation of the distributed power supply, greatly improves the effective operation time and the utilization efficiency of the distributed power supply, reduces the campus power utilization burden when the campus power grid is in short supply, and improves the power utilization economy; under special conditions such as large power grid faults and disasters, the off-grid operation of the micro-grid system can ensure the power supply of important campus equipment and improve the power supply reliability; through power supply optimization configuration, the influence of power grid fluctuation on the lithium battery pack is greatly weakened, the service life of the lithium battery pack is prolonged, and the reliable and stable operation of a micro-grid is ensured.
The photovoltaic and fan energy source scheduling system can realize effective utilization and scheduling of photovoltaic and fan energy sources; the hybrid energy storage method is intelligently controlled by the control method; the hybrid energy storage unit is characterized by bidirectional inversion, can supply power to a load, can be used as a regulating and supporting unit, can absorb energy as the load, and has the function of an emergency power supply (UPS); when the power grid is in power failure, the system can realize the off-grid island load-carrying function; the hybrid energy storage unit in the island mode is used as a main voltage source to provide stable voltage and frequency support for a local load, so that the safe and stable operation of a load system is ensured; the micro-grid system has perfect communication, monitoring, management, control, early warning and protection functions, can continuously and safely operate for a long time, can detect the operation state of the system through the upper computer, and has rich data analysis functions.
Drawings
Fig. 1 is a schematic structural diagram of an embodiment of the system of the present invention.
FIG. 2 is a schematic model diagram of a hybrid energy storage unit according to the present invention; wherein (a) is a lithium battery model; (b) is a super capacitor model.
Illustration of the drawings: 1. a photovoltaic system; 101. a photovoltaic panel; 102. a wind generating set; 103. a grid-connected inverter; 2. a hybrid energy storage unit; 201. a lithium battery pack; 202. a super capacitor; 203. a power distribution cabinet; 3. charging piles; 4. a street lamp.
Detailed Description
The invention is further described below with reference to the figures and the specific embodiments of the description.
As shown in fig. 1, the wind and photovoltaic storage and charging campus microgrid system of the present embodiment includes a distributed power generation unit and a hybrid energy storage unit 2, wherein the distributed power generation unit is connected to the hybrid energy storage unit 2; the distributed power generation unit comprises a photovoltaic system 1 and a wind generating set, and the hybrid energy storage unit 2 comprises a super capacitor 202 and a lithium battery pack 201. Specifically, the photovoltaic panels 101 in the photovoltaic system 1 are respectively laid on the photovoltaic car shed, the building roof in the campus and the street lamps 4, and the building roof photovoltaic system 1 is independently and locally grid-connected. The photovoltaic system 1 is connected to the grid through the grid-connected inverter 103 and is connected to the hybrid energy storage unit 2 through the power distribution cabinet 203. In addition, the microgrid system is provided with charging piles 3 including direct current fast charging piles and alternating current slow charging piles. The wind turbine in the wind turbine generator set 102 adopts a horizontal axis wind turbine generator set 102 and a vertical axis wind turbine. The hybrid energy storage unit 2 adopts a hybrid energy storage mode combining a lithium battery pack 201 and a super capacitor 202. Because traditional single lithium cell energy storage system is easily influenced by power station and load supply and demand relation unbalance, causes power supply system unstability, and the phenomenon of overcharge, overdischarge easily appear in the lithium cell. The hybrid energy storage unit 2 of the super capacitor-lithium battery pack can give full play to the advantages of two energy storage modes to form complementary advantages, the lithium battery pack 201 has the characteristics of high energy density, small instant release power and short service life, the super capacitor 202 has the characteristics of small energy density, large instant release power and long service life, after the two are combined, high-frequency and fluctuating power in a load can be distributed to the super capacitor 202 for supply, and the lithium battery pack 201 mainly provides a low-frequency part in the power due to short service life and limited charging and discharging times. When the hybrid energy storage system works, the distributed power generation units preferentially supply power to loads, the residual electric quantity charges the hybrid energy storage unit 2, and if the distributed power generation units still have residual output power, the residual power is used for surfing the internet. The microgrid system is interconnected with a low-voltage bus of a high-voltage power distribution room of a park through a transformer, and grid connection is realized through a step-up transformer. The charging pile 3 is directly powered through the outgoing line of the low-voltage bus of the high-voltage power distribution room.
The micro-grid system can utilize the stored energy of the hybrid energy storage unit 2 to carry out peak clipping and valley filling, can solve the problem of output fluctuation of the distributed power generation units, greatly improves the effective operation time and the utilization efficiency of the distributed power generation units, reduces the campus power utilization burden when the campus power grid is in short supply, and improves the power utilization economy; under special conditions such as large power grid faults and disasters, the off-grid operation of the micro-grid system can ensure the power supply of important campus equipment and improve the power supply reliability; through power supply optimization configuration, the influence of power grid fluctuation on the lithium battery pack 201 is greatly weakened, the service life of the lithium battery pack 201 is prolonged, and reliable and stable operation of a micro-grid is guaranteed.
The invention also discloses a control method of the wind-solar storage and charging campus micro-grid system, which is used for controlling the micro-grid system to be seamlessly switched between a grid-connected mode and an off-grid mode, and comprises the following specific processes:
the method comprises the following steps of (I) in a grid-connected mode:
(a) when the energy of the photovoltaic system 1 (photovoltaic, the same below) and the wind generating set 102 (fan, the same below) is sufficient
The photovoltaic and the fan are preferentially supplied to a local load for use, the residual energy charges the hybrid energy storage unit 2, and if the residual energy is still supplied to the grid;
(b) when the photovoltaic and the fan are insufficient in energy
When the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the photovoltaic/fan and the hybrid energy storage unit 2 simultaneously supply power to the load; when the SOC of the hybrid energy storage unit is smaller than a set value A, the photovoltaic/fan and the power grid supply power for the load at the same time, and meanwhile, the power grid charges the hybrid energy storage unit 2;
(c) when photovoltaic and fan energy is not available
When the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the hybrid energy storage unit 2 supplies power to a load; when the SOC of the hybrid energy storage unit is smaller than the set value A, the power grid supplies power to the load, and meanwhile, the power grid charges the hybrid energy storage unit 2;
(II) in an off-grid mode:
(a) when the photovoltaic and the fan energy are sufficient
The photovoltaic and the fan are preferentially supplied to the load for use, the residual energy charges the hybrid energy storage unit 2, and if the residual energy still exists, the EMS energy management system limits the power output of the photovoltaic and the fan.
(b) When the photovoltaic and the fan are insufficient in energy
When the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the photovoltaic/fan and the hybrid energy storage unit 2 simultaneously supply power to the load;
when the SOC of the hybrid energy storage unit is less than a set value A, the system limits the power consumption of the controllable load and keeps the power supply of the important load;
when the hybrid energy storage unit SOC is equal to the set value B, the system stops power supply until the electric quantity of the hybrid energy storage unit 2 is restored to the set value, and normal power supply is resumed.
(c) When photovoltaic and fan energy is not available
When the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the hybrid energy storage unit 2 supplies power to a load;
when the SOC of the hybrid energy storage unit is less than a set value A, the system limits the power consumption of the controllable load and reserves the power supply of the important load;
when the hybrid energy storage unit SOC is equal to the set value B, the system stops power supply until the electric quantity of the hybrid energy storage unit 2 is restored to the set value, and normal power supply is resumed.
The photovoltaic and fan energy source scheduling system can realize effective utilization and scheduling of photovoltaic and fan energy sources; the hybrid energy storage method is intelligently controlled by the control method; the hybrid energy storage unit 2 is characterized by bidirectional inversion, can supply power to a load, can be used as a regulating and supporting unit, can absorb energy as the load, and has the function of an emergency power supply (UPS); when the power grid is in power failure, the system can realize the off-grid island load-carrying function; in the island mode, the hybrid energy storage unit 2 serves as a main voltage source to provide stable voltage and frequency support for a local load, so that safe and stable operation of a load system is ensured; the micro-grid system has perfect communication, monitoring, management, control, early warning and protection functions, can continuously and safely operate for a long time, can detect the operation state of the system through the upper computer, and has rich data analysis functions.
Further, in order to ensure safe and reliable operation of the micro-grid hybrid energy storage unit 2, the hybrid energy storage unit 2 of the super capacitor 202-lithium battery pack 201 needs to be optimally controlled, and a hybrid energy optimal management method based on reinforcement learning is provided, and the specific process is as follows:
fig. 2(a) shows a lithium battery model comprising an RC network, an internal resistance and an Open Circuit Voltage (OCV), the state space equation being:
Figure BDA0002605598830000061
wherein R isiInternal resistance, which explains the accumulation and dissipation of charge in the electric double layer; cD、RDAnd UDRepresenting capacitance, resistance and voltage, for explaining the diffusion phenomenon; i.e. iLRepresents the total current; u shapetRepresenting the termination voltage.
FIG. 2(b) shows a model of super capacitor 202, where super capacitor 202 may be formed by an ideal capacitor and resistor RcThe composition is described by a model, and the corresponding physical equation is as follows:
Uct＝Uco-Rcic
wherein icRepresents the load current; u shapecoRepresenting an ideal capacitor voltage; u shapectRepresenting the termination voltage.
To discretize the state variables, the diffusion voltage and the remaining charge (SoC) of the battery are discretized into:
Figure BDA0002605598830000071
wherein, UD(k) Diffusion voltage at time k, soc (k) remaining capacity at time k, and QbIndicates the capacity, eta of the battery packbRepresenting the coulomb efficiency of the cell, Δ t the sampling interval, τbatRepresenting the battery time constant.
The voltage state (SoV) of supercapacitor 202 may be derived from the following equation:
SoV(k+1)＝SoV(k)-ic(k)Δt/Cu
wherein, CuIs the supercapacitor 202 capacity.
The optimization problem is how to obtain a series of optimal action variables a (k) with minimum cost, wherein the cost comprises the energy loss of the lithium battery pack 201, the energy loss of the super capacitor 202 and the energy loss of the DC/DC conversion module, and is represented as follows:
Figure BDA0002605598830000072
where N represents the number of movement cycles and L represents the instantaneous loss, including the battery energy loss Lb(k) Energy loss L of super capacitor 202c(k) And DC/DC converter loss Ldcdc(k) The loss function is expressed as follows:
Figure BDA0002605598830000073
wherein eta isdcdc(k) Representing the efficiency, P, of the DC/DC converterbat(k) For the output power of the lithium battery, z is a logical value, which is 1 when charging and 0 when discharging.
One basic step in reinforcement learning based power management is modeling the required power. The required power can be modeled as a stationary markov chain and the power transition probability matrix can be calculated by nearest neighbor and maximum likelihood estimation as follows:
Figure BDA0002605598830000074
wherein M isi,jRepresents from
Figure BDA0002605598830000075
To
Figure BDA0002605598830000076
Number of transfers of, MiRepresents from
Figure BDA0002605598830000077
Total number of transfers.
Reinforcement learning algorithms are processes of learning from interactions with the goal of maximizing the numeric reward signal and making the best choice through trial and error. In the present invention, the state variable stIs power, SoC and SoV, the current of the battery is the action variable atA reward function rtIs the total energy loss of the hybrid energy system.
The value of state s is defined as follows, which can be considered as a discounted sum of rewards
Figure BDA0002605598830000081
Wherein γ ∈ [0,1]]Represents a discount factor, rt+1Indicating the prize at time t + 1. When the value of state s is optimal, the value function is rewritten as:
Figure BDA0002605598830000082
wherein,
Figure BDA0002605598830000083
representing the probability of transition from state s to state s',
Figure BDA0002605598830000084
representing the reward for transitioning from state s to state s'.
Determining an optimal strategy according to:
Figure BDA0002605598830000085
further, an optimal Q value, referred to as an optimal state-action value, is defined as shown in the following equation:
Figure BDA0002605598830000086
the Q value remains updated according to the following rule:
Q(s,a)＝Q(s,a)+α(r(s,a)+γmaxa'Q(s',a')-Q(s,a))
wherein alpha is a decline factor of [0,1 ].
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.

Claims (8)

1. A campus micro-grid system for wind and light storage and charging is characterized by comprising distributed power generation units and hybrid energy storage units, wherein the distributed power generation units are connected with the hybrid energy storage units; the distributed power generation unit comprises a photovoltaic system and a wind generating set, and the hybrid energy storage unit comprises a super capacitor and a lithium battery pack.
2. The control method of the wind-solar storage and charging campus micro-grid system as claimed in claim 1, characterized by controlling the wind-solar storage and charging campus micro-grid system to switch between a grid-connected mode and an off-grid mode, wherein in the grid-connected mode:
when the energy of the photovoltaic system and the wind generating set is sufficient, the energy is preferentially supplied to a local load for use, the residual energy is used for charging the hybrid energy storage unit, and if the energy still remains, the hybrid energy storage unit is transmitted to the grid;
when the energy of the photovoltaic system and the wind generating set is insufficient and the SOC of the hybrid energy storage unit is more than or equal to a set value A, the distributed power generation unit and the hybrid energy storage unit simultaneously supply power to the load; when the SOC of the hybrid energy storage unit is smaller than a set value A, the distributed generation unit and the power grid supply power for the load at the same time, and the power grid charges the energy storage system at the same time;
when the energy of the photovoltaic system and the wind generating set is not available, and when the SOC of the hybrid energy storage unit is more than or equal to a set value A, the hybrid energy storage unit supplies power to a load; and when the SOC of the hybrid energy storage unit is less than the set value A, the power grid supplies power to the load, and simultaneously charges the hybrid energy storage unit.
3. The control method of the wind-solar storage and charging campus microgrid system according to claim 2, characterized in that in an off-grid mode:
when the energy of the photovoltaic system and the wind generating set is sufficient, the energy is preferentially supplied to a load for use, the residual energy charges the hybrid energy storage unit, and if the energy still remains, the power output of the photovoltaic system and the wind generating set is limited;
when the energy of the photovoltaic system and the wind generating set is insufficient,
when the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the distributed power generation unit and the hybrid energy storage unit simultaneously supply power to the load;
when the SOC of the hybrid energy storage unit is less than a set value A, the power consumption of the controllable load is limited, and the power supply of the important load is reserved;
when the SOC of the hybrid energy storage unit is equal to a set value B, stopping power supply until the electric quantity of the hybrid energy storage unit is recovered to the set value, and recovering normal power supply;
when the photovoltaic system and the wind generating set are without energy,
when the SOC of the hybrid energy storage unit is larger than or equal to a set value A, the hybrid energy storage unit supplies power to a load;
when the SOC of the hybrid energy storage unit is less than a set value A, the power consumption of the controllable load is limited, and the power supply of the important load is reserved;
and when the SOC of the hybrid energy storage unit is equal to the set value B, stopping power supply until the electric quantity of the hybrid energy storage unit is recovered to the set value, and recovering normal power supply.
4. The control method of the wind-solar energy storage and charging campus micro-grid system according to claim 2, wherein power of the hybrid energy storage unit, SoC and SoV are used as state variables stThe current of the lithium battery pack is used as an action variable atThe total energy loss of the hybrid energy storage unit as a reward function rtAnd performing power optimization based on reinforcement learning.
5. The control method of the wind-solar storage and charging campus micro-grid system according to claim 4, wherein the power management method based on reinforcement learning specifically comprises:
the value of state s is defined as follows, which can be considered as a discounted sum of rewards
Figure FDA0002605598820000021
Wherein γ ∈ [0,1]]Represents a discount factor, rt+1Represents the reward at time t + 1; when the value of state s is optimal, the value function is rewritten as:
Figure FDA0002605598820000022
wherein,
Figure FDA0002605598820000023
representing the probability of transition from state s to state s',
Figure FDA0002605598820000024
represents a reward for transitioning from state s to state s';
determining an optimal strategy according to:
Figure FDA0002605598820000025
the optimal Q value for the optimal state-action value is defined as follows:
Figure FDA0002605598820000026
the Q value remains updated according to the following rule:
Q(s,a)＝Q(s,a)+α(r(s,a)+γmaxa'Q(s',a')-Q(s,a))
wherein alpha is a decline factor of [0,1 ].
6. The method for controlling the wind-solar energy storage and charging campus microgrid system of claim 5, wherein power modeling is a smooth Markov chain, and the power transition probability matrix can be calculated by a nearest neighbor method and a maximum likelihood estimation method as follows:
Figure FDA0002605598820000027
wherein M isi,jRepresents from
Figure FDA0002605598820000028
To
Figure FDA0002605598820000029
Number of transfers of, MiRepresents from
Figure FDA00026055988200000210
Total number of transfers.
7. The method for controlling the wind-solar storage and charging campus microgrid system according to claim 5, characterized in that a state variable s is settDiscretizing, namely discretizing diffusion voltage and residual electric quantity SoC of the lithium battery pack into:
Figure FDA00026055988200000211
wherein, UD(k) Diffusion voltage at time k, soc (k) remaining capacity at time k, and QbIndicates the capacity, eta of the battery packbRepresenting the coulomb efficiency of the cell, Δ t the sampling interval, τbatRepresents a battery time constant;
the voltage state SoV of the super capacitor can be derived from the following equation:
SoV(k+1)＝SoV(k)-ic(k)Δt/Cu
wherein, CuIs the super capacitor capacity.
8. The control method of the wind-solar energy storage and charging campus microgrid system as claimed in claim 5, wherein a series of optimal action variables a (k) are obtained with minimum cost during power optimization, wherein the cost includes lithium battery pack energy loss, super capacitor energy loss and DC/DC conversion module energy loss, and is represented as follows:
Figure FDA0002605598820000031
where N represents the number of movement cycles and L represents the instantaneous loss, including the battery energy loss Lb(k) Energy loss L of super capacitorc(k) And DC/DC converter loss Ldcdc(k) The loss function is expressed as follows:
Figure FDA0002605598820000032
wherein eta isdcdc(k) Representing the efficiency, P, of the DC/DC converterbat(k) For the output power of the lithium battery, z is a logical value, which is 1 when charging and 0 when discharging.
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