CN105914886A - Distributed energy cloud networking intelligent control method and system - Google Patents
Distributed energy cloud networking intelligent control method and system Download PDFInfo
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- CN105914886A CN105914886A CN201610328238.6A CN201610328238A CN105914886A CN 105914886 A CN105914886 A CN 105914886A CN 201610328238 A CN201610328238 A CN 201610328238A CN 105914886 A CN105914886 A CN 105914886A
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- H02J13/0013—
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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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
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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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- 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
- 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
- H02J2310/62—The condition being non-electrical, e.g. temperature
- H02J2310/64—The condition being economic, e.g. tariff based load management
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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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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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
- 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
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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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
- 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
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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
- 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
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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
- 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
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
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- Supply And Distribution Of Alternating Current (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a distributed energy cloud networking intelligent control method and a distributed energy cloud networking intelligent control system. The distributed energy cloud networking intelligent control method comprises the steps of: acquiring an optimal electric price curve, dividing time periods, allocating optimal allocation output or optimal allocation load to energy subnet at different time periods, controlling power generation equipment to generate power according to the maximum output for each energy subnet, and charging charging equipment when the charging equipment plugs into a charging pile; and controlling energy storage equipment to adjust actual output and actual load of the energy subnets. The distributed energy cloud networking intelligent control system comprises a central scheduling decision-making unit, an energy cloud networking allocation unit and a distributed decision-making execution unit. The distributed energy cloud networking intelligent control method and the distributed energy cloud networking intelligent control system achieve the effects of reducing excess load and output surplus by taking the energy subnets as a unit based on controlling the controllable loads such as the energy storage equipment in the energy subnets and the charging pile, achieve the purposes of power grid load balancing, peak shaving and load shifting, can prevent charging of various kinds of large-scale charging equipment from affecting peak of the power grid, achieving efficient/ optimized configuration of energy resources, and enhance social and economic benefits.
Description
Technical field
The present invention relates to power scheduling technology, be specifically related to a kind of distributed energy cloud networking intelligent control method and system.
Background technology
Electric power system dispatching is to ensure that the work of power network safety operation, external reliable power supply, all kinds of power generation is carried out and a kind of effective management means of using in order.Electric power system dispatching is to be provided electric energy by many power plants, is powered to users by transmission of electricity, power transformation, distribution, supply network, is a complicated system.Its production, supply and sales process completes the most simultaneously and is balancing.Therefore, its scheduler task is different from general commercial production scheduling.Electric power system dispatching to keep the balance of generating and load at any time, it is desirable to each department in dispatching management scope is strictly completed scheduler task according to quantity by matter.
Electrical network is in running, network load in one time can present the shape of curve, the time period (such as 17:00 ~ 20:30) that often network load is higher in curve occurs that load exceeds the quata, and there is load surplus in the time period that network load is relatively low in curve (such as 2:00 in morning ~ 5:30), but whether load exceeds the quata or load surplus, all there is serious harm in the safe operation for electrical network.On the one hand therefore, during dispatching of power netwoks, commercial power for the different time periods has carried out the mode that segmentation is negotiated a price, and reduces load exceed the quata and the purpose of load surplus for being affected the electricity consumption time period of user by price.But aforesaid way exceeds the quata still inadequate with load surplus effect for reducing load, is not enough to solve the load balancing problem of electrical network.
Summary of the invention
The technical problem to be solved in the present invention: for the problems referred to above of prior art, there is provided a kind of to realize reduction load in units of energy subnet is exceeded the quata and load surplus based on the control of generating equipment, energy storage device and charging pile in energy subnet, reach network load equilibrium, the purpose of peak load shifting, it is prevented from the impact on electrical network peak of charging of all kinds of large-scale charger, realize the energy efficient/distribute rationally, promote the distributed energy cloud networking intelligent control method and system of economic results in society.
In order to solve above-mentioned technical problem, the technical solution used in the present invention is:
A kind of distributed energy cloud networking intelligent control method, step includes:
1) superior control centre obtains and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
2) it was divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, the workload demand dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
3) for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；
4) in each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load.
Preferably, the detailed step of described step 4) includes:
4.1) in each time period for each energy subnet, it is judged that optimal allocation is exerted oneself and whether optimal allocation load is 0, if optimal allocation is exerted oneself and optimal allocation load is 0, then execution step 4.2 is redirected)；If optimal allocation load is non-zero, optimal allocation is exerted oneself is 0, then redirect execution step 4.3)；If optimal allocation load is 0, optimal allocation is exerted oneself non-zero, then redirect execution step 4.4)；
4.2) judging whether the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of energy subnet has surplus, if there being surplus, selecting energy storage device to be charged until all energy storage devices are full of；Wane without the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of surplus and energy subnet, then select energy storage device to carry out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.3) judge whether electrical equipment and the charging pile load sum of energy subnet current slot are set up less than optimal allocation load, if setting up and the electricity price of exerting oneself of current slot being more than load electricity price, then the energy storage device of energy subnet is selected to be charged until all energy storage devices are full of；Otherwise, for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judging the overload of current slot energy subnet, selection energy storage device carries out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.4) judge that the generating equipment of energy subnet current slot exerts oneself to exert oneself less than optimal allocation whether to set up, if set up and the electricity price of exerting oneself of current slot is more than load electricity price, then the energy storage device of energy subnet is selected to carry out discharging until all energy storage device discharge offs；Otherwise, the energy storage device selecting energy subnet stops electric discharge until generating equipment is exerted oneself and exerts oneself equal to optimal allocation in the maximum electric discharge load sum of the energy storage device of electric discharge；Redirect execution step 4.1).
Preferably, the detailed step being charged, according to the principle distribution time period that the low electricity price time period is preferential, the charger allowing automatic distribution charging interval section in described step 3) includes:
S1) determine the charging duration of charger, whether allow the interaction request of time-sharing charging under overload condition to user's output, and obtain the interaction results that user selects；
S2) according to the principle that the low electricity price time period is preferential be charger distribute charging interval section；
S3) be charger distribution each charging interval section, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of time period energy subnet, so that it is determined that cause the charger that energy subnet overloads；
S4) for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of current slot energy subnet；If current slot overloads, then to the charger causing energy subnet to overload, the charger of time-sharing charging under overload condition is allowed to carry out time-sharing multiplex charging, adjust and reduce and allow the charging service expense of the charger of time-sharing charging under overload condition, adjust the charging service expense increasing the charger causing energy subnet to overload；Current slot does not overloads else if, then be directly charged all of charger；Finally, the charging duration at charger stops being charged charger after reaching.
Preferably, described step S2) detailed step include:
S2.1) export charge mode to the user of charger and select request, charge mode includes instant charge mode, manual reservation protocol and automatic reservation protocol, user selects instant charge mode then to redirect execution step S2.2), user selects manual reservation protocol then to redirect execution step S2.3), user selects automatic reservation protocol then to redirect execution step S2.4)；
S2.2) select at least one time period from now on as the time period that charger is charged according to the charging duration of charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.3) request is selected to user's output time section of charger, time period user selected is as the time period being charged charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.4) for each time period, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum electric discharge load of energy storage device of electric discharge, external electrical network, the net capability sum of energy subnet, as actual gross capability, is deducted actual gross capability actual total load and obtains the load difference of exerting oneself of energy subnet；First using the load difference time period more than 0 of exerting oneself as non-over loading section clipping time, never over loading section clipping time selects the time period as distributing to the charging interval section of charger according to electricity price priority level from low to high, if this time period meets the charging duration of all chargers, redirect execution step S3)；If non-over loading section clipping time can not meet charger charging duration or all time periods be exert oneself load difference less than or equal to 0 over loading section clipping time, then select the time period as the charging interval section distributing to charger according to electricity price priority level from low to high from over loading section clipping time, export the non-over loading disabled prompting of section clipping time to user, redirect execution step S3).
Preferably, described step S2.4) in when user exports the disabled prompting of non-over loading section clipping time, also include the increase-volume suggestion exporting energy subnet.
The present invention also provides for a kind of distributed energy cloud networking intelligence control system, including:
Central schedule decision package, obtains for superior control centre and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
Energy cloud networking allocation unit, for being divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, workload demand needed for being dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
Distributed decision making performance element, for for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；In each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load.
The present invention has an advantage that
1, the present invention divides the time period according to according to the best electric price curve, demand of exerting oneself needed for higher level control centre is dispatched, workload demand distributes to each energy subnet according to the time period, achieve by with electric power networks (energy, the energy) and internet (information, data) the intelligent distributed energy demand end that connects, supply side carries out interconnecting of energy and signal, organic coupling, response Real-Time Scheduling instruction (or electricity price curve), based on generating equipment in energy subnet, the control of the controllable burden such as energy storage device and charging pile realizes exceeding the quata reduction load in units of energy subnet and load surplus, realize the energy efficient/distribute rationally, network load equilibrium can be reached, the purpose of peak load shifting, promote economic results in society.
2, the present invention obtains the best electric price curve as one-level with superior control centre, divide the time period and distribution optimal allocation is exerted oneself or optimal allocation load is two grades, the discharge and recharge controlling power generation, charger charging and energy storage device is three grades, form the distributed energy cloud networking Intelligent Control Strategy of three grades, it is thus possible to realize the distributed energy cloud networking Based Intelligent Control in units of energy subnet flexibly and easily, it is possible to realize the regional agency formula way to manage of electric energy conveniently and efficiently.
3, the present invention will be divided into different time sections according to electricity price, demand of exerting oneself, workload demand needed for being dispatched higher level control centre distribute to each energy subnet according to the time period, obtain energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, then in units of the time period and in load limit, generating equipment, energy storage device and charging pile are carried out integrated dispatch, network load equilibrium, the purpose of peak load shifting can be reached, it is possible to prevent the impact on electrical network peak of charging of all kinds of large-scale charger.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of embodiment of the present invention method.
Fig. 2 is embodiment of the present invention method step 4) schematic flow sheet.
Fig. 3 is the structural representation of embodiment of the present invention system.
Detailed description of the invention
As it is shown in figure 1, the step of the present embodiment distributed energy cloud networking intelligent control method includes:
1) superior control centre obtains and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
2) it was divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, the workload demand dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
3) for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；
4) in each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load.
nullThe present embodiment obtains the best electric price curve as one-level with superior control centre，Divide the time period and distribution optimal allocation is exerted oneself or optimal allocation load is two grades，Control power generation、The discharge and recharge of charger charging and energy storage device is three grades，Form the distributed energy cloud networking Intelligent Control Strategy of three grades，And in each time period，Discharge by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation、Control energy storage device to be charged regulating the actual of energy subnet exert oneself and actual load when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load，By with electric power networks (energy、The energy) and internet (information、Data) the intelligent distributed energy demand end that connects、Supply side carries out interconnecting of energy and signal、Organic coupling，Response Real-Time Scheduling instruction (or electricity price curve)，Control based on energy subnet realizes exceeding the quata reduction load in units of energy subnet and load surplus，Demand of exerting oneself needed for the scheduling of response higher level control centre、Workload demand，Realize the energy efficient/distribute rationally，Promote economic results in society，And in units of the time period, carry out integrated dispatch，Network load equilibrium can be reached、The purpose of peak load shifting，It is prevented from the impact on electrical network peak of charging of all kinds of large-scale charger.
In the present embodiment, the detailed step being charged, according to the principle distribution time period that the low electricity price time period is preferential, the charger allowing automatic distribution charging interval section in step 3) includes:
S1) determine the charging duration of charger, whether allow the interaction request of time-sharing charging under overload condition to user's output, and obtain the interaction results that user selects；
S2) according to the principle that the low electricity price time period is preferential be charger distribute charging interval section；
S3) be charger distribution each charging interval section, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of time period energy subnet, so that it is determined that cause the charger that energy subnet overloads；
S4) for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of current slot energy subnet；If current slot overloads, then to the charger causing energy subnet to overload, the charger of time-sharing charging under overload condition is allowed to carry out time-sharing multiplex charging, adjust and reduce and allow the charging service expense of the charger of time-sharing charging under overload condition, adjust the charging service expense increasing the charger causing energy subnet to overload；Current slot does not overloads else if, then be directly charged all of charger；Finally, the charging duration at charger stops being charged charger after reaching.
The present embodiment passes through above-mentioned steps S1)～S3), achieve and in load limit, all chargers are charged, therefore, it is possible to effectively prevent the quantity impact on network load of charger, reach network load equilibrium, the purpose of peak load shifting, if maximum charge load summation is more than load limit, the mode then using timesharing is charged the maximum charge load summation so that current slot any moment all chargers less than load limit to all of charger, the charging of more charger can be capable of under limited load limit, thus more preferable charging ability is provided on the premise of limited resources.
In the present embodiment, step S2) detailed step include:
S2.1) export charge mode to the user of charger and select request, charge mode includes instant charge mode, manual reservation protocol and automatic reservation protocol, user selects instant charge mode then to redirect execution step S2.2), user selects manual reservation protocol then to redirect execution step S2.3), user selects automatic reservation protocol then to redirect execution step S2.4)；
S2.2) select at least one time period from now on as the time period that charger is charged according to the charging duration of charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.3) request is selected to user's output time section of charger, time period user selected is as the time period being charged charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.4) for each time period, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum electric discharge load of energy storage device of electric discharge, external electrical network, the net capability sum of energy subnet, as actual gross capability, is deducted actual gross capability actual total load and obtains the load difference of exerting oneself of energy subnet；First using the load difference time period more than 0 of exerting oneself as non-over loading section clipping time, never over loading section clipping time selects the time period as distributing to the charging interval section of charger according to electricity price priority level from low to high, if this time period meets the charging duration of all chargers, redirect execution step S3)；If non-over loading section clipping time can not meet charger charging duration or all time periods be exert oneself load difference less than or equal to 0 over loading section clipping time, then select the time period as the charging interval section distributing to charger according to electricity price priority level from low to high from over loading section clipping time, export the non-over loading disabled prompting of section clipping time to user, redirect execution step S3).
By above-mentioned steps S2.1)～S2.4), achieve instant charge mode, manual reservation protocol, automatically the time period selection strategy of reservation protocol Three models, it is thus possible to realize quick charge (instant charge mode), on-demand charging (manual reservation protocol) and with the network minimal charging (automatic reservation protocol) as target of charging, and user can select electricity price relatively low time period voluntarily under manual reservation protocol, automatically reservation protocol the most never can select the time period according to electricity price priority level from low to high in over loading section clipping time, integrated dispatch is carried out in units of the time period, network load equilibrium can be reached, the purpose of peak load shifting, it is prevented from the impact on electrical network peak of charging of all kinds of large-scale charger.nullThe present embodiment above-mentioned steps S2.4) in，Solution 0-1 knapsack problem just it is evolved into by specifying which charging electric vehicle，According to arrive first first by principle after charging gun plugged by certain electric automobile，Platform is i.e. charged presetting，If selecting automatic reservation protocol，The method that then basis is progressively retrodicted is that it distributes time period，The most never over loading section clipping time selects the time period according to electricity price priority level from low to high，Interval according to the best electric price、Suboptimum electricity price is interval、Par is interval、The punishment electricity price interval distribution time period，If non-over loading section clipping time can not meet the charging duration of all chargers or all time periods are over loading section clipping time，Then from over loading section clipping time, select the time period according to electricity price priority level from low to high，Therefore, it is possible to reach network load equilibrium on the basis of ensureing user's charging、The purpose of peak load shifting，Prevent the impact on electrical network peak of charging of all kinds of large-scale charger.In the present embodiment, step S2.4) in when user exports the disabled prompting of non-over loading section clipping time, also include the increase-volume suggestion exporting energy subnet.
As in figure 2 it is shown, the detailed step of the present embodiment step 4) includes:
4.1) in each time period for each energy subnet, it is judged that optimal allocation is exerted oneself and whether optimal allocation load is 0, if optimal allocation is exerted oneself and optimal allocation load is 0, then execution step 4.2 is redirected)；If optimal allocation load is non-zero, optimal allocation is exerted oneself is 0, then redirect execution step 4.3)；If optimal allocation load is 0, optimal allocation is exerted oneself non-zero, then redirect execution step 4.4)；
4.2) judging whether the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of energy subnet has surplus, if there being surplus, selecting energy storage device to be charged until all energy storage devices are full of；Wane without the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of surplus and energy subnet, then select energy storage device to carry out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.3) judge whether electrical equipment and the charging pile load sum of energy subnet current slot are set up less than optimal allocation load, if setting up and the electricity price of exerting oneself of current slot being more than load electricity price, then the energy storage device of energy subnet is selected to be charged until all energy storage devices are full of；Otherwise, for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judging the overload of current slot energy subnet, selection energy storage device carries out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.4) judge that the generating equipment of energy subnet current slot exerts oneself to exert oneself less than optimal allocation whether to set up, if set up and the electricity price of exerting oneself of current slot is more than load electricity price, then the energy storage device of energy subnet is selected to carry out discharging until all energy storage device discharge offs；Otherwise, the energy storage device selecting energy subnet stops electric discharge until generating equipment is exerted oneself and exerts oneself equal to optimal allocation in the maximum electric discharge load sum of the energy storage device of electric discharge；Redirect execution step 4.1).
As it is shown on figure 3, the distributed energy cloud networking intelligence control system of the present embodiment includes:
Central schedule decision package, obtains for superior control centre and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
Energy cloud networking allocation unit, for being divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, workload demand needed for being dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
Distributed decision making performance element, for for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；In each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load
The present embodiment is positioned to respond middle operator and the concrete actuator that higher level control centre (provincial control centre) instructs, it is divided into the information end that central schedule decision package, energy cloud networking allocation unit, distributed decision making performance element three are constituted, and the energy source that generating equipment, energy storage device and charging pile and user are constituted.The magnanimity information treatment in situ such as people-car-load-generating are preserved by the energy cloud networking allocation unit of information end, distributed decision making performance element, by big data and cloud computing, analyze different power consumer and the life of generating equipment and with, send out energy characteristic, by core data teletransmissions such as load limits to central schedule decision package, so that central schedule decision package is added up backward subdispatch center (provincial control centre) and is declared load limit, to realize and the interaction at subdispatch center (provincial control centre) and obtain preferential electricity price.Can source then realize quantity of electricity on-site elimination, central schedule decision package can issue dispatch command according to Network congestion, sensitive analysis, load prediction, electricity price curve etc., under power network security runs premise, preferentially dissolve with clean energy resource, generate electricity-use can the overall economic benefit such as maximization of economic benefit as target, optimal control production capacity, with can, energy storage overall process.When central schedule decision package determines load limit and electricity price, following manner can be selected as required: (1) platform calculates decision-making: cloud networked platforms is according to short-term load forecasting, calculate in conjunction with optimal load flow and sensitive analysis, identification is obstructed or limited section, issues power mode or instruction is cut-off in energy storage-generating.Platform typically needs electrical network parameter, exerts oneself and the information such as power load, historical data in real time from host computer, and general platform is difficult to meet this function, and it is power-management centre, provincial region that this functional module is generally at least.(2) platform obtains scheduling decision: platform interconnects with provincial control centre, directly obtain electricity consumption, the energy storage forwarding electricity etc. issued control centre to instruct, accessed equipment and the user of this cloud networked platforms by scanning, declare load limit to control centre, obtain license and preferential electricity price.(3) given load limit, determines electricity price according to electricity price curve.Energy cloud networking allocation unit accesses the resource (generating, energy storage and electrical equipment) of cloud networking according to the load limit determined, electricity price, distributes hair and energy storage information to different energy sources subnet.Distributed decision making performance element receives the load limit that energy cloud networking allocation unit is specified, the resource accessed according to this energy subnet, sends generating-energy storage-electricity consumption (charging) instruction.If generating equipment disclosure satisfy that actual load and has load surplus during exerting oneself, then send energy storage instruction, if actual load can not be met, then send electricity consumption (charging) instruction.
In the present embodiment, energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；Generating equipment can select photo-voltaic power generation station, wind power station etc., and when generated output, generating equipment generates electricity according to EIAJ；Energy storage device can select pump-up power station, super capacitor, accumulator etc., for according to energy subnet exert oneself and difference (wane load) between the exerting oneself of difference (surplus load), actual load and energy subnet between actual load controls energy storage, the conversion of generating.Charging pile is for the big battery capacity electric vehicles such as electric automobile/electric tool charging.
The present embodiment also including, information predicts unit, for issuing optimum charging (electricity consumption) suggestion to user, especially to often send heavy duty zone, obstruction, the user of heavy load region charging stagger the time, misplace charging suggestion, improves efficiency.
In sum, the present embodiment constitutes the distributed energy cloud networked system using energy subnet as node, form one containing distributed photovoltaic power generation, Intelligent charging spot, micro-energy cloud networking node of electrokinetic cell energy storage, according to the best electric price curve and the charger acceptable charging interval (input), (maximally utilize photovoltaic charged with electricity price profit maximization as target, utilize civil power on a small quantity), control energy storage and the charging process of energy storage device, simultaneously response emergency management and rescue demand.Intelligent distributed energy demand end by connecting with electric power networks (energy, the energy) and internet (information, data), supply side are carried out the interconnecting of energy and signal, organic mate by the present embodiment, response Real-Time Scheduling instruction (or electricity price curve), participate in the quantity of electricity transaction of intelligent grid, peak load shifting, reach the energy efficient, distribute rationally, objective economic benefit can not only be brought, good Consumer's Experience and social education, user can also be brought to cultivate benefit simultaneously.
The above is only the preferred embodiment of the present invention, and protection scope of the present invention is not limited merely to above-described embodiment, and all technical schemes belonged under thinking of the present invention belong to protection scope of the present invention.It should be pointed out that, for those skilled in the art, some improvements and modifications without departing from the principles of the present invention, these improvements and modifications also should be regarded as protection scope of the present invention.
Claims (6)
1. a distributed energy cloud networking intelligent control method, it is characterised in that step includes:
1) superior control centre obtains and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
2) it was divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, the workload demand dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
3) for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；
4) in each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load.
Distributed energy cloud the most according to claim 1 networking intelligent control method, it is characterised in that the detailed step of described step 4) includes:
4.1) in each time period for each energy subnet, it is judged that optimal allocation is exerted oneself and whether optimal allocation load is 0, if optimal allocation is exerted oneself and optimal allocation load is 0, then execution step 4.2 is redirected)；If optimal allocation load is non-zero, optimal allocation is exerted oneself is 0, then redirect execution step 4.3)；If optimal allocation load is 0, optimal allocation is exerted oneself non-zero, then redirect execution step 4.4)；
4.2) judging whether the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of energy subnet has surplus, if there being surplus, selecting energy storage device to be charged until all energy storage devices are full of；Wane without the exert oneself load sum of the load and charging pile of comparing electrical equipment of the generating equipment of surplus and energy subnet, then select energy storage device to carry out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.3) judge whether electrical equipment and the charging pile load sum of energy subnet current slot are set up less than optimal allocation load, if setting up and the electricity price of exerting oneself of current slot being more than load electricity price, then the energy storage device of energy subnet is selected to be charged until all energy storage devices are full of；Otherwise, for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judging the overload of current slot energy subnet, selection energy storage device carries out discharging until all energy storage device discharge offs；Redirect execution step 4.1)；
4.4) judge that the generating equipment of energy subnet current slot exerts oneself to exert oneself less than optimal allocation whether to set up, if set up and the electricity price of exerting oneself of current slot is more than load electricity price, then the energy storage device of energy subnet is selected to carry out discharging until all energy storage device discharge offs；Otherwise, the energy storage device selecting energy subnet stops electric discharge until generating equipment is exerted oneself and exerts oneself equal to optimal allocation in the maximum electric discharge load sum of the energy storage device of electric discharge；Redirect execution step 4.1).
Distributed energy cloud the most according to claim 1 and 2 networking intelligent control method, it is characterized in that, the detailed step being charged, according to the principle distribution time period that the low electricity price time period is preferential, the charger allowing automatic distribution charging interval section in described step 3) includes:
S1) determine the charging duration of charger, whether allow the interaction request of time-sharing charging under overload condition to user's output, and obtain the interaction results that user selects；
S2) according to the principle that the low electricity price time period is preferential be charger distribute charging interval section；
S3) be charger distribution each charging interval section, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of time period energy subnet, so that it is determined that cause the charger that energy subnet overloads；
S4) for current slot, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum load that discharges of energy storage device of electric discharge, external electrical network to the net capability sum of energy subnet as actual gross capability；If the actual total load of current slot is more than actual gross capability, then judge the overload of current slot energy subnet；If current slot overloads, then to the charger causing energy subnet to overload, the charger of time-sharing charging under overload condition is allowed to carry out time-sharing multiplex charging, adjust and reduce and allow the charging service expense of the charger of time-sharing charging under overload condition, adjust the charging service expense increasing the charger causing energy subnet to overload；Current slot does not overloads else if, then be directly charged all of charger；Finally, the charging duration at charger stops being charged charger after reaching.
Distributed energy cloud the most according to claim 3 networking intelligent control method, it is characterised in that described step S2) detailed step include:
S2.1) export charge mode to the user of charger and select request, charge mode includes instant charge mode, manual reservation protocol and automatic reservation protocol, user selects instant charge mode then to redirect execution step S2.2), user selects manual reservation protocol then to redirect execution step S2.3), user selects automatic reservation protocol then to redirect execution step S2.4)；
S2.2) select at least one time period from now on as the time period that charger is charged according to the charging duration of charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.3) request is selected to user's output time section of charger, time period user selected is as the time period being charged charger, if the maximum charge load summation overload of energy subnet all chargers of electrical equipment and this time period of selection within the time period selected, export overload prompting to user, redirect execution step S3)；
S2.4) for each time period, using the power load of electrical equipment of energy subnet, the maximum charge load of charging pile, in the maximum charge load sum of energy storage device of charging as actual total load, the generating equipment of the electrical equipment of energy subnet is exerted oneself, in the maximum electric discharge load of energy storage device of electric discharge, external electrical network, the net capability sum of energy subnet, as actual gross capability, is deducted actual gross capability actual total load and obtains the load difference of exerting oneself of energy subnet；First using the load difference time period more than 0 of exerting oneself as non-over loading section clipping time, never over loading section clipping time selects the time period as distributing to the charging interval section of charger according to electricity price priority level from low to high, if this time period meets the charging duration of all chargers, redirect execution step S3)；If non-over loading section clipping time can not meet charger charging duration or all time periods be exert oneself load difference less than or equal to 0 over loading section clipping time, then select the time period as the charging interval section distributing to charger according to electricity price priority level from low to high from over loading section clipping time, export the non-over loading disabled prompting of section clipping time to user, redirect execution step S3).
Distributed energy cloud the most according to claim 4 networking intelligent control method, it is characterised in that described step S2.4) in user export non-over loading section clipping time disabled prompting time, also include export energy subnet increase-volume suggestion.
6. a distributed energy cloud networking intelligence control system, it is characterised in that including:
Central schedule decision package, obtains for superior control centre and exerts oneself demand, workload demand and the best electric price curve, described the best electric price curve include one day in the electricity price information of exerting oneself of different time and load electricity price information；
Energy cloud networking allocation unit, for being divided into the different time periods according to according to the best electric price curve by one day 24 hours, demand of exerting oneself, workload demand needed for being dispatched higher level control centre distribute to each energy subnet according to the time period, obtaining energy subnet to exert oneself or optimal allocation load in the optimal allocation of different time sections, described energy subnet includes generating equipment, energy storage device, electrical equipment and charging pile；
Distributed decision making performance element, for for each energy subnet, control generating equipment carry out generating electricity, detecting whether charging pile has charger to insert according to EIAJ, if any charger insert then in the case of energy subnet nonoverload, according to the low electricity price time period preferential principle distribution the time period to permission automatic distribution charging interval section charger be charged；In each time period, control energy storage device by controlling energy storage device when the generating equipment of energy subnet is exerted oneself and exerted oneself less than optimal allocation and carrying out discharging, when the electrical equipment of energy subnet and charging pile load sum are less than optimal allocation load and be charged regulating the actual of energy subnet and exert oneself and actual load.
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