CN103633739B - Microgrid energy management system and method - Google Patents

Microgrid energy management system and method Download PDF

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Publication number
CN103633739B
CN103633739B CN201310618411.2A CN201310618411A CN103633739B CN 103633739 B CN103633739 B CN 103633739B CN 201310618411 A CN201310618411 A CN 201310618411A CN 103633739 B CN103633739 B CN 103633739B
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micro
capacitance sensor
analysis
energy
information
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CN201310618411.2A
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Chinese (zh)
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CN103633739A (en
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崔琼
舒杰
吴志锋
黄磊
姜桂秀
张继元
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中国科学院广州能源研究所
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Abstract

The invention discloses a microgrid energy management system which comprises an information collection and data preprocessing unit, a network analysis unit and an energy optimization unit, wherein the information collection and data preprocessing unit performs data mining preprocessing on information, collected by SCADA/PMU mixed measurement, by adopting a CIM model and combining historical section management, the network analysis unit is used for realizing mixed measurement-based microgrid state estimation on the basis of network topology analysis, performing risk analysis and assessment and sensitivity analysis to realize early warning and warning for failure threat, and adopting corresponding precautionary measures or performing emergency control, and the energy optimization unit is used for performing microgrid energy optimization scheduling by combining forecast information and system operation analysis according to the information of the microgrid state estimation. The invention also provides a method which adopts the microgrid energy management system to perform microgrid energy management. The functions of the microgrid energy management system are further perfected, and the system safety, the power supply reliability and the system control accuracy and effectiveness of a microgrid are improved.

Description

A kind of microgrid energy management system and method
Technical field
The present invention relates to electric power system, particularly a kind of microgrid energy management system and method.
Background technology
Micro-capacitance sensor (Micro Grid); as a kind of novel energy networking supply and management system; the advantage of distributed power generation can be integrated; coordinate the contradiction between distributed generation unit (micro battery) and bulk power grid (referring to the power network be made up of power plant, transformer station, grid, distribution transformer and low-voltage line road network etc.); make full use of various Distributed Power Resource; in conjunction with local load, energy storage device and associated monitoring and protective device, the novel electric power micro-system of formation.The EMS of micro-capacitance sensor is monitored to the running status of equipment in micro-capacitance sensor, corresponding control strategy is formulated according to current system ruuning situation and control objectives, for the feature of exerting oneself of micro battery, adopt rational energy-optimised technology that micro battery is maximized the use, give full play to micro-capacitance sensor low-carbon (LC), economic advantage.
In existing microgrid energy management system, the SCADA laying particular emphasis on monitoring system steady operation situation is only adopted to carry out information gathering and the monitoring of micro-capacitance sensor, also lack unified markers accurately between the monitoring result of different location, be difficult to carry out overall dynamics analysis to total system.Secondly, SCADA cannot realize the function of the data correlation device model information gathered, and the storage of data is just based on time series, and itself is without model information.Along with the development of various generation technology, the kind of micro battery constantly increases and changes, and the frequency that micro-capacitance sensor increased and reconstructed micro battery newly is also relatively high.Along with going deep into of all kinds of micro-capacitance sensor management system application, there is the application bottleneck of information integration, between each management system information incompatible, can not intercommunication, information model disunity, can not the integrated management information of macroscopic view.Therefore, need to adopt Mixed measurements system to carry out information gathering, line number of going forward side by side Data preprocess, realize carrying out Simultaneous Monitoring to micro-grid system state, for network analysis and control provide Data Source.
The micro battery power generation characteristics such as solar cell and blower fan are different, cause generating voltage, electric current momentary fluctuation large, and can be subject to the impact of the factors such as geographical environment, weather and time and make output have very large randomness and fluctuation.Secondly, in micro-capacitance sensor, load neither be unalterable, and constantly can change along with time, weather and economic dispatch factor, this makes the energy exchange processes in micro-capacitance sensor between micro battery and load become more complicated.Therefore, need to adopt the energy-optimised unit based on forecast information, monitor and managment is carried out to the energy flow of system, optimize the inner each micro battery of micro-grid system, energy-storage units and and bulk power grid between the direction of energy flow and amplitude, to improve the power supply quality of system, the economic feature of environmental protection.
With micro battery, miniaturized and quantity mostly is feature to micro-capacitance sensor, has disperseed schedule risk, but in micro-capacitance sensor, the condition such as the energy output of wind-force, photovoltaic cells and weather conditions, ambient temperature, wind speed, solar radiation amount is closely related; The failure rate of generating equipment is also with environmental condition and time variations, and these random factors all can produce certain impact to the fail safe of micro-grid system, power supply reliability.Thus the multiple-energy-source micro-capacitance sensor of the intermittent micro battery such as wind energy, solar energy is comprised, if the consideration that its dispatching patcher is simple lays particular emphasis on the energy scheduling of economy, exist significantly not enough, need to carry out network analysis to micro-grid system, to improve micro-capacitance sensor fail safe, power supply reliability.
For this reason, for generating randomness, the unsteadiness of micro battery, the destabilizing factor of these micro-capacitance sensor such as the mobility of load, need the distributed system to this complexity of micro-capacitance sensor, a kind of microgrid energy management system is proposed, carry out system status monitoring, safety analysis, energy-optimised scheduling, to improve security of system, power supply reliability, the economic feature of environmental protection of micro-capacitance sensor.
Summary of the invention
An object of the present invention proposes a kind of microgrid energy management system, carries out overall monitor to micro-grid system state, realizes prediction data in micro-grid system, in real time and the Centralizing inspection of historical data; Network analysis is carried out to improve the security of system of micro-capacitance sensor to micro-grid system; According to the information of micro-capacitance sensor state estimation, in conjunction with forecast information and system cloud gray model analysis, carry out the power flow management of micro-capacitance sensor, realize multiple-energy-source and optimize complementary, Multi-value coordination control.
For achieving the above object, the concrete technical scheme that the present invention takes is:
A kind of microgrid energy management system, it comprises:
Information gathering and data pre-processing unit, for gathering each unit simulation amount of micro-capacitance sensor and switching value data, Weather information, phasor data, and the EMS data of connected electrical network; In conjunction with CIM, management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter;
Network analysis element, in conjunction with the model of described integration, figure and parameter, carries out the micro-capacitance sensor state estimation based on hybrid measurement, asks for micro-capacitance sensor state variable; According to micro-capacitance sensor state variable and control variables, and in conjunction with the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, predict potential fault, quantize the adjustment factor eliminating the out-of-limit fault of trend; By early warning and alarm module, danger, failure condition are warned with sound, light mode, and promptly takes corresponding precautionary measures or carry out emergency control; Described hybrid measurement comprises SCADA and measures and PMU measurement;
Energy-optimised unit, for the information according to described micro-capacitance sensor state estimation, in conjunction with micro battery generating forecast, Load Forecasting, the forecast of energy-storage units energy state and system cloud gray model analysis, carries out the power flow management of micro-capacitance sensor;
Wherein, described information gathering and data pre-processing unit comprise:
SCADA module, for SCADA data acquisition and Monitor and Control, wherein, described SCADA data acquisition comprises the collection of each unit simulation amount of micro-capacitance sensor and switching value, Weather information, and described Monitor and Control comprises that equipment controls, measures, parameter regulates;
PMU module, for the synchronous acquisition of phasor data; Described phasor data comprises the configuration node of phasor measuring set and voltage phasor, the electric current phasor of transmission line;
CIM, for describing relation between each unit of micro-capacitance sensor and logical construction thereof, realizing information exchange between the inner and different-energy management system of microgrid energy management system and sharing;
Historic Section administration module, for the EMS data based on the data of described SCADA module acquires, the phasor data of PMU module acquires and connected electrical network, in conjunction with CIM, carry out data mining preliminary treatment, integrate micro-capacitance sensor Historic Section information, described micro-capacitance sensor Historic Section information is the set of the micro-capacitance sensor model structure of historical juncture, running status and electricity consumption condition information;
Described network analysis element comprises:
Network topology module, for the folding condition according to switch element, determines the electric connecting relation of each element in micro-grid system, and in conjunction with described micro-capacitance sensor Historic Section information, forms network topological diagram;
Based on the state estimation module of hybrid measurement, for the basis at Network topology, according to the data of described SCADA module acquires, and the phasor data of PMU module acquires, ask for electric network state variable;
Risk analysis evaluation module, for quantizing the factor causing random faule in micro-grid system, the consequence brought after estimating described random faule, set up can characterization system risk quantizating index and carry out calculating, analyzing, described in cause the factor of random faule to include but not limited to weather conditions, element state;
Sensitivity analysis module, draw for utilizing sensitivity calculations and to change with control variables and relation between the state variable that changes and control variables, instruct fast for providing the prevention and control of dangerous situation, simultaneously for the elimination of the out-of-limit fault of trend provides the adjustment foundation of quantification;
Described energy-optimised unit comprises:
Load Forecasting module, for according to the historical load data in described micro-capacitance sensor Historic Section information, and considers weather forecast information, date category, carries out the prediction consuming electric energy;
Micro battery generating forecast module, for photovoltaic power prediction and wind power prediction;
Energy-storage units forecast module, for predicting the energy state of energy-storage units, so that analyze the power conversion of micro-capacitance sensor and storage capacity, described energy state comprises the energy of energy that energy-storage units stores and release;
Micro-grid system operating analysis module, for according to the micro-capacitance sensor state estimation information from described network analysis element, carries out the fail-safe analysis of micro-capacitance sensor, power quality analysis and economic feature of environmental protection analysis;
Micro-capacitance sensor Optimized Operation module, for the forecast information of comprehensive micro battery generating forecast, Load Forecasting, energy-storage units energy state, on the basis of micro-grid system operating analysis and network analysis, the operational mode different for system and control objectives, export optimum results, concrete dispatch command is provided to each unit; Described control objectives comprises reliability optimum, the economic feature of environmental protection is optimum.
Described fail-safe analysis is on the basis of the system safety situation drawn based on risk analysis assessment and sensitivity analysis, for micro-capacitance sensor islet operation pattern, analyze micro-grid system and fail the workload demand that meets and the ratio of total capacity requirement in the analysis and assessment phase.
Described power quality analysis at least comprises line voltage, mains by harmonics, grid voltage three-phase imbalance, the impact of reactive balance and the DC component of the grid-connected injection wherein one on the impact of micro-capacitance sensor.
Described economic feature of environmental protection analysis at least comprises the wherein one in economic benefit, environmental benefit and comprehensive benefit analysis thereof, and described comprehensive benefit is the summation of economic benefit and environmental benefit.
The each unit of described micro-capacitance sensor is respectively micro battery, energy-storage units, load cell, switch element, protective relaying device, current transformer, transmission line.
Described state variable is node voltage amplitude and phase angle, and described control variables comprises the output terminal voltage of the meritorious of micro battery and idle power output and micro battery.
Described optimum results comprises micro battery power, energy-storage units fills/put power, power is thrown/cut to the mutual power between micro-capacitance sensor and bulk power grid, controllable type load.
Another object of the present invention is to provide a kind of energy management method for micro-grid, comprehensively monitors micro-grid system state; Realize the safety analysis to micro-grid system; Carry out the power flow management of micro-capacitance sensor, realize multiple-energy-source and optimize complementary, Multi-value coordination control.
For achieving the above object, the concrete technical scheme that the present invention takes is:
A kind of energy management method for micro-grid, it comprises the following steps:
Step 1, the collection each unit simulation amount of micro-capacitance sensor and switching value data, Weather information, phasor data, and the EMS data of connected electrical network; In conjunction with CIM, management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter;
Step 2, model, figure and parameter in conjunction with described integration, carry out the micro-capacitance sensor state estimation based on hybrid measurement, ask for micro-capacitance sensor state variable; According to micro-capacitance sensor state variable and control variables, and in conjunction with the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, predict potential fault, quantize the adjustment factor eliminating the out-of-limit fault of trend; By early warning and alarm module, danger, failure condition are warned with sound, light mode, and promptly takes corresponding precautionary measures or carry out emergency control; Described hybrid measurement comprises SCADA and measures and PMU measurement;
Step 3, information according to described micro-capacitance sensor state estimation, forecast and system cloud gray model analysis in conjunction with micro battery generating forecast, Load Forecasting, energy-storage units energy state, carry out the power flow management of micro-capacitance sensor;
Wherein, step 1 comprises:
Step 11, SCADA data acquisition and Monitor and Control, wherein, described SCADA data acquisition comprises the collection of each unit simulation amount of micro-capacitance sensor and switching value, Weather information, and described Monitor and Control comprises that equipment controls, measures, parameter regulates;
The synchronous acquisition of step 12, phasor data, described phasor data comprises the configuration node of phasor measuring set and voltage phasor, the electric current phasor of transmission line;
Relation between step 13, each unit of description micro-capacitance sensor and logical construction thereof, realize the information exchange between microgrid energy management system inside and different-energy management system and share;
Step 14, EMS data based on the data of described SCADA module acquires, the phasor data of PMU module acquires and connected electrical network, in conjunction with CIM, carry out data mining preliminary treatment, integrate micro-capacitance sensor Historic Section information, described micro-capacitance sensor Historic Section information is the set of the micro-capacitance sensor model structure of historical juncture, running status and electricity consumption condition information;
Described step 2 comprises:
Step 21, folding condition according to switch element, determine the electric connecting relation of each element in micro-grid system, and in conjunction with described micro-capacitance sensor Historic Section information, form network topological diagram;
Step 22, on the basis of Network topology, according to the data of described SCADA module acquires, and the phasor data of PMU module acquires, ask for electric network state variable;
The factor of random faule is caused in step 23, quantification micro-grid system, the consequence brought after estimating described random faule, set up can characterization system risk quantizating index and carry out calculating, analyzing, described in cause the factor of random faule to include but not limited to weather conditions, element state;
Step 24, utilize sensitivity calculations to draw to change with control variables and relation between the state variable that changes and control variables, instruct fast for providing the prevention and control of dangerous situation, simultaneously for the elimination of the out-of-limit fault of trend provides the adjustment foundation of quantification;
Described step 3 comprises:
Step 31, according to the historical load data in described micro-capacitance sensor Historic Section information, and consider weather forecast information, date category, carry out the prediction consuming electric energy;
The prediction of step 32, photovoltaic power and wind power prediction;
Step 33, predict the energy state of energy-storage units, so that analyze the power conversion of micro-capacitance sensor and storage capacity, described energy state comprises the energy of energy that energy-storage units stores and release;
Step 34, basis, from the micro-capacitance sensor state estimation information of described network analysis element, carry out the fail-safe analysis of micro-capacitance sensor, power quality analysis and economic feature of environmental protection analysis;
The forecast information of step 35, comprehensive micro battery generating forecast, Load Forecasting, energy-storage units energy state, on the basis of micro-grid system operating analysis and network analysis, the operational mode different for system and control objectives, export optimum results, provide concrete dispatch command to each unit; Described control objectives comprises reliability optimum, the economic feature of environmental protection is optimum.
The invention has the advantages that: the function improving microgrid energy management system further, improve the security of system of micro-capacitance sensor, power supply reliability, the precision of Systematical control and validity.
Accompanying drawing illustrates:
Fig. 1 is the structured flowchart of a kind of microgrid energy management system of the present invention;
Fig. 2 is the schematic diagram of the function of a kind of microgrid energy management system of the present invention;
Fig. 3 is the flow chart of a kind of energy management method for micro-grid of the present invention.
Embodiment:
The present invention is described in detail with specific embodiment with reference to the accompanying drawings below, but not as a limitation of the invention.
As shown in Figure 1, microgrid energy management system, be connected with each unit of micro-capacitance sensor by PLC, sensor hardware device, it comprises support platform layer, modeling analysis layer, application function layer, human-machine interface layer, four levels.
1. support platform layer, comprises operating system, data base administration, network service, safety management.
Operating system, meet the requirement of electrical energy metering management, system has been completely free of the dependence to particular hardware platform, supports the multiple operating platforms such as WINDOWSNT/2000/XP/2003/Linux.
The database of system adopts in real time/historical data base and PI (Plant Information) real-time dataBase system.The present invention, based on CIM, adopts Object-oriented Technique, with reference to IEC61970 associated international standards, sets up a set of PI real-time data base based on CIM.Utilize Historic Section administration module, by system real-time/historical data is associated with electric network model, forms the Historic Section of electrical network, the senior applied function module for system is analyzed used.
General TCP/IP, X.25, the procotol such as HTTP, support various standard interface; Be suitable for the international standards such as high-level programming language such as SQL database language and C/C++.
User class adopts rights management and password mechanism, controls the operation that different users can carry out; Strict operation auditing flow: password, privilege analysis, operation acknowledgement, timeout treatment.
2. modeling analysis layer, comprises micro-capacitance sensor state estimation, sensitivity analysis, risk analysis assessment, load prediction, generating prediction, energy storage energy predicting and Optimal Operation Model.By micro-capacitance sensor state estimation model comprehensive sensitivity analysis and risk analysis assessment models storehouse, provide a series of man-rate modes about micro-grid system network analysis, realize micro-grid system and control decision-premaking, to improve security of system; Obtain information of forecasting by forecast model, collaborative real time information, carries out analog simulation to different energy scheduling modes by Optimal Operation Model storehouse, the operational mode different for system and control objectives, selects optimal scheduling mode.
3. application function layer, each model basis that they are set up based on modeling analysis layer is developed, under the support of support platform, completes correlation function.Comprise:
(1) graphic monitoring module: adopt the international standards such as advanced 3-D graphic openGL or OSF/Motif; Achieve the functions such as free convergent-divergent, translation, rolling, roaming, multiwindow; Freely being socketed and quick directly mouse control of multi-screen; Rapid navigation and freedom of information display mechanism; Full Chinese character, word, table, figure can select arbitrarily the function of color and third party's graphic decomposed.
(2) system safety assessment module: in micro-grid system, the random fault of equipment is often unpredictable, and load also has uncertainty.The consequence of fault may cause local and even large-area power failure, has had a strong impact on the fail safe of micro-grid system.Utilize risk analysis to assess, set up the quantizating index of energy characterization system safety; Utilize sensitivity analysis, calculate and to change with control variables and the state variable relation between the two that changes, quantize the adjustment factor of the out-of-limit Failure elimination of trend; Realize the Integral safety evaluation to system.
(3) system cloud gray model evaluation module: its function realizes the fail-safe analysis of system, power quality analysis and economic feature of environmental protection analysis, and be presented in man-machine interface by analysis result.
(4) energy-optimised scheduler module: the selection realizing reliability optimum, the optimum different control objectives of the economic feature of environmental protection; Consider the system running pattern of micro-grid connection and isolated island, the network analysis of comprehensive micro-capacitance sensor and system cloud gray model analysis, for described control objectives, be configured the compound mode of each micro battery; Energy distribution is carried out to the exerting oneself of each micro battery, energy storage device; Energy reversal allocation result for the different operational mode of system and control objectives is shown in man-machine interface.
(5) conservative management module; when the wind-powered electricity generation unit of micro-capacitance sensor, photovoltaic cells, DC/DC module group, grid-connected converter are inner or energy storage device and management system thereof break down; automatically complete the protection under failure condition respectively, fault message is presented in man-machine interface simultaneously.The impact that dispatching patcher may cause system according to fault, the error protection of executive system level.
(6) alarm bulletin module: various types of affair alarm record, involution record, user's login record, control operation record, system condition record are provided.Event type comprises: accident, fault, shape become, out-of-limit, protection event; Warning information can be divided into accident, exception, informs, information four class layering alarm display, can carry out comprehensive inquiry by conditions such as equipment, event type, event level, time of origins.There is provided by equipment, one by one, whole three kinds of alert event confirmation methods, can automatic or manual confirm.
(7) report capability module: the editor and the management that realize form.Form comprises voltameter, various limit value table, schedule of trains, system operation situation statistical form and operational factor table; Special time period form, daily sheet, the moon form; Various protection information and form; Control operation process record and form.
4. human-machine interface layer, comprise display real-time status, Historic Section, forecast information, described forecast information comprises: generating forecast, Load Forecasting and the forecast of energy storage energy state; Comprise safety analysis, early warning and warning, prevention and emergency control interface, namely show the result of risk analysis assessment and sensitivity analysis, risk of disturbance information is reported to the police, realize the remote operation of precautionary measures or emergency control; Also comprise operating analysis interface, i.e. the result of surveillance operating analysis; In Optimized Operation interface, realize different control objectives and select, and monitoring is under selected control objectives, the compound mode of micro battery and respective situation of exerting oneself, and the energy state of energy storage device and configuring condition.
Fig. 2 is shown in by the microgrid energy management system structure chart of this example.Microgrid energy management system of the present invention comprises information gathering and data pre-processing unit, network analysis element, energy-optimised unit, the functional module corresponding to each unit and operation principle as follows:
One, information gathering and data pre-processing unit:
The information gathered comprises each unit simulation amount of micro-capacitance sensor, switching value data, Weather information, phasor data, and the EMS data of connected electrical network; Described Information Monitoring, pass through CIM, data sharing and exchange can be carried out between the EMS that microgrid energy management system is inner and different, and then the electrical quantity information of Real-Time Monitoring micro-capacitance sensor and other electrical network connected nodes, ensure the security and stability of energy exchange between micro-capacitance sensor and connected electrical network; Management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter.Information gathering and the concrete functional module of data pre-processing unit as follows:
1.SCADA module: data acquisition and supervisor control, mainly completes the collection of each unit simulation amount of micro-capacitance sensor, switching value data and Weather information; Equipment control, measurement, parameter regulate and various signal alarm function.The each unit simulation amount of described micro-capacitance sensor, switching value data mainly comprise voltage, electric current, the power of micro battery, the state parameter of energy-storage module, the power of each stage load in load cell, the on off state of element, the warning of each unit and early warning signal.
2.PMU module: by the synchronous phasor measuring device based on GPS, carries out the synchronous acquisition of phasor data, and with unified markers, carries out Simultaneous Monitoring to micro-grid system state; Overcome in SCADA observation process, owing to lacking unified markers accurately between the monitoring result that causes of difference of monitoring place, be difficult to carry out overall dynamics analysis to total system, system simulation model also can only carry out by offline mode the problem that corrects; The synchronous phasor measurement algorithm adopted mainly comprises: based on the phasor measurement algorithm of least square method, digital differentiation, Kalman filtering method, based on Fourier algorithm interpolation method, utilize small echo to calculate phasor information; Described phasor data mainly comprises micro-grid system node and transmission line voltage phasor, electric current phasor.
3.CIM model: in micro-capacitance sensor, the kind of micro battery can constantly increase along with the development of various generation technology and change, and the frequency that micro-capacitance sensor increased and reconstructed micro battery newly is also relatively high.Therefore, along with going deep into of all kinds of micro-capacitance sensor management system application, there is the application bottleneck of information integration, having comprised: between each management system information incompatible, can not intercommunication, information model disunity, can not the integrated management information of macroscopic view.For solving the problem, the present invention increases CIM function, for describing relation between each unit of micro-capacitance sensor and logical construction thereof, there is provided a kind of with object class and attribute and between relation represent the standard method of micro-grid system resource, achieve the information exchange between microgrid energy management system inside and different-energy management system and share, and then the electrical quantity information of Real-Time Monitoring micro-capacitance sensor and other electrical network connected nodes, ensure the security and stability of energy exchange between micro-capacitance sensor and connected electrical network.Adopt comprehensive Object-Oriented Model technology, namely each object in micro-capacitance sensor is described with UML, in this model, definition CIM bag, contain class and the attribute of one or more object in each bag of CIM, describe these objects relation each other simultaneously.Described CIM bag mainly comprises generating bag, load model bag, measurement bag, topology bag, power transmission line bag, protection package, bag of stopping using.
4. Historic Section administration module: in existing EMS, cannot realize the function of the data correlation device model information gathered.The storage of data is just based on time series, and itself can not obtain comprehensive Historic Section information without model information only by data interaction bus.Therefore for effectively to manage described Information Monitoring, make it be associated with device model information, and provide high-quality, comprehensive, continuous, correct data message, the present invention with the addition of Historic Section administration module.It is based on the EMS data of CIM, SCADA data, phasor data, the electrical network that is connected, supply a model to association, data merging, data modifier, data mend the data prediction function of recruiting, achieve the integrated of described Information Monitoring, to form Historic Section, the application for next step provides the model of integration, figure and parameter.Described Historic Section information is the data acquisition system of the micro-capacitance sensor model structure of historical juncture, running status and information on load; Described data merge the measuring point data fracture referring to and change for equipment replacement or upgrading, measuring point and cause, and merge, the data of the old and new's measuring point to ensure the continuity of data; Described data modifier, comprises Correctness Analysis and the deburring of data; Described data are mended and recruited is mend to recruit historical data to ensure the integrality of data.
Two, network analysis element:
Excavation Cluster Based on Network Analysis platform, comprehensively from Integrated Models, figure, the parameter information of information gathering and data pre-processing unit, carries out the state estimation of micro-capacitance sensor, asks for micro-capacitance sensor state variable; According to described micro-capacitance sensor state variable and control variables, in conjunction with the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, realize micro-grid system and control decision-premaking, instruct micro-grid system controlling run, improve the fail safe of micro-grid system.The concrete functional module of network analysis element is as follows:
1. Network topology module: according to the folding condition of switch element, determines the electric connecting relation of each element of micro-grid system, forms network topological diagram.In conjunction with Historic Section administration module, network topology platform can be got the sectional model of any time, on figure, then carry out the displaying of this moment model.Micro-capacitance sensor dispatching management personnel can carry out the selection of micro-capacitance sensor operational mode on this basis, then can carry out the storage of information section.Other senior applied function module, can this section of far call in conjunction with real time data, analyzing as risk analysis assessment and sensitivity analysis, and result of calculation can turn back in man-machine interface and show.
2., based on the state estimation module of hybrid measurement: the wide area system be made up of phasor measurement unit (PMU) and SCADA system coexist, the admixture be made up of difference measurement character of formation is estimated.Overcome the data that traditional state estimation gathers according to SCADA, be difficult to ensure real-time and the problem not possessing the synchronous advantage in strange land.PMU introduces wherein by the present invention, and the number of configuration phasor measuring set makes the whole network Observable, and now real-time measurement amount and required quantity of state are linear relationship, can improve state estimation accuracy and runtime, realizes real-time online estimation.On the basis of Network topology, premised on micro-capacitance sensor observability, according to equivalent electrical network, component parameters, the analog quantity that SCADA system provides measures, and the phasor data of PMU collocation point, asks for micro-capacitance sensor state variable.Described equivalent electrical network is the open and-shut mode according to switch element, through the micro-capacitance sensor structural model that Network topology is formed; Described component parameters mainly comprises transmission line, the resistance of equipment, reactance, susceptance parameter; The measurement that described SCADA system provides comprises node and injects meritorious, reactive power, and branch road is meritorious, reactive power, voltage, current amplitude; Described micro-capacitance sensor state variable comprises node voltage amplitude and phase angle.
3. risk analysis evaluation module: in the actual motion of micro-capacitance sensor, the probability of malfunction of each equipment is different and along with the operational mode of the operational mode of micro-grid system, each equipment, operating condition, external environmental factor and changing.Therefore, increase risk analysis evaluation function in the present invention, consider the health status of micro-capacitance sensor equipment, obtained facility information is converted into corresponding equipment state or fault type; Correlation between apparatus for establishing, micro-grid system, external factor; Quantification may cause the factor of random faule, the consequence brought after suspected fault; Final set up can characterization system risk quantizating index and carry out calculating, analyzing, instruct the scheduling decision-premaking of micro-capacitance sensor, improve the fail safe of micro-grid system.The health status information of described equipment except comprise that information gathering and data pre-processing unit gather in real time and historical plant status information, also comprise rigging up and debugging record, record of examination, on-the-spot patrol record.For assessment and the diagnostic method of equipment, mainly contain Bayesian network analysis method, evidence theory information fusion, fuzzy logic, expert system, K nearest neighbor algorithm, neural net, support vector cassification method at present.
4. sensitivity analysis: in order to carry out prevention and control fast to the unsafe condition occurred in micro-capacitance sensor, simultaneously for the elimination of the out-of-limit fault of trend provides the adjustment foundation of quantification, the present invention proposes to adopt sensitivity analysis module, by sensitivity calculations, reflect the linearisation relation between all kinds of mode variable in micro-capacitance sensor trend.When the state variable of system in micro-capacitance sensor changes along with control variables generation minor variations, employing sensitivity describes variation relation between the two.Described control variables comprises the output terminal voltage of meritorious, idle power output, the micro battery of micro battery.Described state variable comprises node voltage amplitude and phase angle.Utilize sensitivity analysis, the weak cells of electrical network can be judged quickly and accurately; Calculate micro battery, the load sensitivity about the out-of-limit branch road of trend, analytical calculation draws the adjustment amount eliminating out-of-limit micro battery active power fast on this basis, overload is removed, or draw the scheme of excision load, make dispatching management personnel early, promptly take corresponding precautionary measures or carry out emergency control.
Further, described network analysis element also comprises early warning and alarm module, comprehensive analysis risk assessment and sensitivity analysis result, dope the unsafe condition that may occur, by danger, failure condition reporting to the police with sound, light mode, simultaneously precautionary measures and emergency control module action, can automatically or the dangerous situation of manual intervention process micro-grid system or emergency, and its priority level is higher than micro-capacitance sensor Optimized Operation module.
Three, energy-optimised unit:
Guarantee on the basis of system safety at micro-grid system network analysis, according to micro-capacitance sensor state estimation information, in conjunction with micro battery generating forecast, Load Forecasting, the forecast of energy-storage units energy state and system cloud gray model analysis, carry out the power flow management of micro-capacitance sensor, realize multiple-energy-source and optimize complementary, Multi-value coordination control.The concrete functional module of energy-optimised unit is as follows:
1. Load Forecasting module: according to historical load data, and consider Weather information, date category, adopt and include but not limited to that Linear regression (ULR), exponential smoothing (ES) and artificial neural network method (ANN) carry out consuming the prediction of electric energy.The system loading of following 0-24 hour certain point can be forecast; Can complete 1 day to 1 week, the time interval be 15 minutes system loading prediction, the time interval can set; While various data prediction on working day is provided, also provide the prediction of common day off (Saturday, Sunday) and festivals or holidays (New Year's Day, the Spring Festival etc.); Can arrange the Start Date of load prediction and prediction number of days, predicting that Start Date both can be some day in the future, also can be the some day of history, and default value is next sky when the day before yesterday, predicts that number of days is the longest and is set to 1 week; Predict the outcome and provide with form and curve two kinds of forms simultaneously, to carry out inquiring about and revising, show maximum predicted load, minimum prediction load and corresponding time of occurrence, consensus forecast load, prediction information about power simultaneously.
2. micro battery generating forecast module: comprise photovoltaic power prediction and wind power prediction.Forecasting Methodology mainly comprises lasting method, time series method, neural net, support vector regression, chaos forecast method, Kalman filtering method, wavelet analysis method, grey method, fuzzy logic method.
The modeling of single time scale power sequence is adopted for generation current prediction, sampling interval is larger, thus reduce model to the problem of power temporal aspect simulation precision, the present invention is based on the little sampling interval power data of (time interval is 1min), adopt a kind of multidimensional time-series Local prediction.The method sets up by multi-dimensional time phase space reconfiguration with based on the support vector regression combination of ant optimization and cross validation the photovoltaic power Local prediction model shifting to an earlier date 0-4 hour.Weather forecast information, history generated output data and HOTTEL fine day solar radiation model calculated value is adopted to carry out photovoltaic power prediction a few days ago.For choosing the highest modeling sample of similarity, adopting the method choice modeling sample of hierarchical screening, setting up the photovoltaic power prediction that dynamic prediction model realizes 1-2 days in advance.Based on the wind power data of little sampling interval (time interval is 1min), by structure wind power innovation sequence, set up ARMAX-GARCH wind power prediction model, realize the wind power prediction of 0-4 hour in advance.Above method all can realize the power average value of resolution changable and the prediction of fluctuation range, improves the accuracy of prediction, confidence level and flexibility ratio.
Photovoltaic power forecast model can carry out 0-4h ultra-short term and 1-3d short term power point prediction and interval prediction in advance in advance; Wind power prediction model can carry out 0-4h ultra-short term power points prediction in advance and interval.Ultra-short term predicted time yardstick is for shifting to an earlier date 5min, 15min, 30min, 1h, 2h, 3h and 4h, and the time interval of short-term forecast is a few days ago 1h.Predict the outcome and provide, to carry out inquiring about and revising with form and curve two kinds of forms simultaneously.Power prediction maximum and corresponding time of occurrence, power prediction mean value, power quantity predicting value information are shown simultaneously for power prediction a few days ago.
3. energy-storage units forecast module: energy state forecast is carried out for energy-storage units such as storage battery, super capacitor, flying wheel batteries, wherein, for the prediction of batteries to store energy state, its model can be divided into two large classes: a class is Method of Physical Modeling, mainly contains discharge test method, Ah counting method, densimetry, open circuit voltage method, internal resistance (conductance) method; Another kind of is System Discrimination and parameter estimation model method, mainly contains neural network, fuzzy logic method, Kalman filtering method, linear model method.For the energy-storage units such as super capacitor, flying wheel battery, then the device characteristics curve mainly relying on producer to provide or the equipment operation curve preset by micro-capacitance sensor control centre carry out the prediction of energy storage state.
4. micro-grid system operating analysis: comprise fail-safe analysis, power quality analysis and economic feature of environmental protection analysis.
Fail-safe analysis is on the basis of the system safety situation exported based on risk analysis assessment and sensitivity analysis, for micro-capacitance sensor islet operation pattern, adopt time series method, the analysis and assessment phase is divided into some equal time slices, think in arbitrary time slice, wind speed, light intensity, load is all stable, and according to energy balance principle, micro battery, the Energy transmission summation of energy-storage units equals load input, the summation of each devices consume power of micro-capacitance sensor, analyze the ratio of the unappeasable workload demand of micro-grid system and workload demand total in the analysis and assessment phase.
Power quality analysis is according to current Power Quality Detection data, analysis and assessment are carried out to the quality of power supply, mainly comprise: the impact on line voltage, the impact on mains by harmonics, on the unbalanced impact of grid voltage three-phase, on the impact of reactive balance and the DC component of grid-connected injection on the impact of electrical network; Formulate the strategy that quality of power supply online compensation controls.
Economic feature of environmental protection analysis: under the prerequisite meeting workload demand, analyzes the economic benefit of micro-capacitance sensor, environmental benefit and comprehensive benefit thereof.Described comprehensive benefit refers to the summation of economic benefit and environmental benefit.Described economic benefit economic index represents, its functional relation is three sum of products, and described three products are products of the product of each micro battery generated output and each product of micro battery operating cost, the power of energy storage device and energy storage device operating cost, Power loss and unit network loss Financial cost.Under equal-wattage, economic index more small economy benefit is better.Described environmental benefit environmental protection index represents, functional relation is the ratio of the conventional electric power generation source Environmental costs of each micro battery and energy storage device and equal-wattage, and described ratio is less, and environmental benefit is larger.
5. micro-capacitance sensor Optimized Operation module: grid-connected and islet operation pattern and the load condition of considering micro-capacitance sensor, the system cloud gray model analysis of comprehensive micro-capacitance sensor and network analysis, the control objectives optimum for the economic feature of environmental protection, reliability is optimum, export optimum results, provide concrete dispatch command to each unit, the associating optimal scheduling realizing each unit of micro-capacitance sensor controls.In economically less developed region, lay particular emphasis on the control objectives selecting economy optimum; At the micro-capacitance sensor that sensitiveness load is relatively many, lay particular emphasis on the control objectives selecting reliability optimum.Described optimum results comprises micro battery power, energy-storage units fills/put power, power is thrown/cut to the mutual power between micro-capacitance sensor and bulk power grid, controllable type load.The economic environmental protection optimization of micro-capacitance sensor belongs to multivariable, nonlinear combinatorial optimization problem.The target function of its Mathematical Modeling and constraints consider output characteristic, workload demand, the Environmental costs aspect of all kinds of micro battery.Main input parameter has technical and economic peculiarities parameter, micro battery unit starting cost, unit operation maintenance cost, the unit emission factor of workload demand, all kinds of micro battery.For different load levels, it is minimum that unit realizes cost by different combinations.By setting up rational economic model, Optimization Solution thus make the economic feature of environmental protection optimized operation plan of described micro-capacitance sensor.Modeling method mainly comprises priority method, dynamic programming, genetic algorithm, particle cluster algorithm, Chaos Ant Colony Optimization.Described reliability optimum refers to that power supply reliability is optimum, is carried out the topology reconstruction of network, improves the reliability optimization index of system, obtain the optimization of system reliability by the folding condition switching micro-capacitance sensor breaker in middle element.Index that the reliability optimization index of described system comprises system System average interruption frequency, system System average interruption duration, system on average power unavailability ratio, the average amount of power supply of system is not enough.The topology reconstruction of described network belongs to multivariable, the nonlinear combinatorial optimization problem of reliability optimization index, and its solution mainly contains branch exchange method, optimal flow pattern, nonlinear integer programming, simulated annealing, genetic algorithm, expert system, artificial neural network method.
As shown in Figure 3, present invention also offers a kind of method adopting said system to carry out microgrid energy management, the method comprises the following steps:
Step 1, the collection each unit simulation amount of micro-capacitance sensor and switching value data, Weather information, phasor data, and the EMS data of connected electrical network; In conjunction with CIM, management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter;
Step 2, model, figure and parameter in conjunction with described integration, carry out the state estimation based on hybrid measurement, ask for electric network state variable; According to described electric network state variable and control variables, and consider the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, predict the dangerous situation that may occur, quantize the adjustment factor of the out-of-limit Failure elimination of trend simultaneously; By early warning and alarm module, danger, failure condition are warned with sound, light mode, promptly takes corresponding precautionary measures or carry out emergency control;
Step 3, information according to described micro-capacitance sensor state estimation, in conjunction with each micro battery generating forecast, Load Forecasting, the forecast of energy-storage units energy state and system cloud gray model analysis, the operational mode different for system and control objectives, ask for each micro battery in system to exert oneself and energy storage device energy distribution, and concrete dispatch command is provided to each unit.
Compare with method with the EMS of prior art micro-capacitance sensor, feature of the present invention specifically comprises:
1. the collection of phasor data.Propose to adopt PMU module, realize the synchronous acquisition of phasor data, be convenient to carry out Simultaneous Monitoring to micro-grid system state; Overcome in SCADA observation process, lack common time accurately and reliably between the monitoring result of different location, be difficult to carry out overall dynamics analysis to total system, system simulation model can only carry out by offline mode the problem that corrects.
2. data prediction function.Propose to adopt the management of CIM, Historic Section, realize data correlation device model information, data integrated, modify, mend and recruit, ensure that the continuity of data, correctness, integrality, the application for next step provides the model of integration, figure and parameter.
3. clearly propose in network analysis element, adopt the state estimation function module under SCADA and PMU hybrid measurement, improve the estimated accuracy of micro-capacitance sensor state; Overcome the data estimation micro-capacitance sensor quantity of state that traditional state estimation gathers according to SCADA, be difficult to ensure real-time and the problem not possessing the synchronous advantage in strange land.
4. clearly propose in network analysis element, carry out risk analysis assessment and sensitivity analysis.Set up the quantizating index of energy characterization system risk and carry out calculating, analyzing, instructing the scheduling decision-premaking of micro-capacitance sensor; Predict potential fault, and promptly take corresponding precautionary measures or carry out emergency control, improve the fail safe of micro-grid system.
5. to carry out fail-safe analysis and the economic feature of environmental protection analysis when clearly proposing micro-grid system operating analysis, and give concrete analysis and evaluation index.
6. clearly propose the method for photovoltaic power prediction, wind power prediction.
Above-listed detailed description is illustrating for possible embodiments of the present invention, and this embodiment is also not used to limit the scope of the claims of the present invention, and the equivalence that all the present invention of disengaging do is implemented or changed, and all should be contained in the scope of the claims of this case.

Claims (8)

1. a microgrid energy management system, is characterized in that, it comprises:
Information gathering and data pre-processing unit, for gathering each unit simulation amount of micro-capacitance sensor and switching value data, Weather information, phasor data, and the EMS data of connected electrical network; In conjunction with CIM, management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter;
Network analysis element, in conjunction with the model of described integration, figure and parameter, carries out the micro-capacitance sensor state estimation based on hybrid measurement, asks for micro-capacitance sensor state variable; According to micro-capacitance sensor state variable and control variables, and in conjunction with the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, predict potential fault, quantize the adjustment factor eliminating the out-of-limit fault of trend; By early warning and alarm module, danger, failure condition are warned with sound, light mode, and promptly takes corresponding precautionary measures or carry out emergency control; Described hybrid measurement comprises SCADA and measures and PMU measurement;
Energy-optimised unit, for the information according to described micro-capacitance sensor state estimation, in conjunction with micro battery generating forecast, Load Forecasting, the forecast of energy-storage units energy state and system cloud gray model analysis, carries out the power flow management of micro-capacitance sensor;
Wherein, described information gathering and data pre-processing unit comprise:
SCADA module, for SCADA data acquisition and Monitor and Control, wherein, described SCADA data acquisition comprises the collection of each unit simulation amount of micro-capacitance sensor and switching value, Weather information, and described Monitor and Control comprises that equipment controls, measures, parameter regulates;
PMU module, for the synchronous acquisition of phasor data; Described phasor data comprises the configuration node of phasor measuring set and voltage phasor, the electric current phasor of transmission line;
CIM, for describing relation between each unit of micro-capacitance sensor and logical construction thereof, realizing information exchange between the inner and different-energy management system of microgrid energy management system and sharing;
Historic Section administration module, for the EMS data based on the data of described SCADA module acquires, the phasor data of PMU module acquires and connected electrical network, in conjunction with CIM, carry out data mining preliminary treatment, integrate micro-capacitance sensor Historic Section information, described micro-capacitance sensor Historic Section information is the set of the micro-capacitance sensor model structure of historical juncture, running status and electricity consumption condition information;
Described network analysis element comprises:
Network topology module, for the folding condition according to switch element, determines the electric connecting relation of each element in micro-grid system, and in conjunction with described micro-capacitance sensor Historic Section information, forms network topological diagram;
Based on the state estimation module of hybrid measurement, for the basis at Network topology, according to the data of described SCADA module acquires, and the phasor data of PMU module acquires, ask for electric network state variable;
Risk analysis evaluation module, for quantizing the factor causing random faule in micro-grid system, the consequence brought after estimating described random faule, set up can characterization system risk quantizating index and carry out calculating, analyzing, described in cause the factor of random faule to include but not limited to weather conditions, element state;
Sensitivity analysis module, draw for utilizing sensitivity calculations and to change with control variables and relation between the state variable that changes and control variables, instruct fast for providing the prevention and control of dangerous situation, simultaneously for the elimination of the out-of-limit fault of trend provides the adjustment foundation of quantification;
Described energy-optimised unit comprises:
Load Forecasting module, for according to the historical load data in described micro-capacitance sensor Historic Section information, and considers weather forecast information, date category, carries out the prediction consuming electric energy;
Micro battery generating forecast module, for photovoltaic power prediction and wind power prediction;
Energy-storage units forecast module, for predicting the energy state of energy-storage units, so that analyze the power conversion of micro-capacitance sensor and storage capacity, described energy state comprises the energy of energy that energy-storage units stores and release;
Micro-grid system operating analysis module, for according to the micro-capacitance sensor state estimation information from described network analysis element, carries out the fail-safe analysis of micro-capacitance sensor, power quality analysis and economic feature of environmental protection analysis;
Micro-capacitance sensor Optimized Operation module, for the forecast information of comprehensive micro battery generating forecast, Load Forecasting, energy-storage units energy state, on the basis of micro-grid system operating analysis and network analysis, the operational mode different for system and control objectives, export optimum results, concrete dispatch command is provided to each unit; Described control objectives comprises reliability optimum, the economic feature of environmental protection is optimum.
2. microgrid energy management system according to claim 1, it is characterized in that, described fail-safe analysis is on the basis of the system safety situation drawn based on risk analysis assessment and sensitivity analysis, for micro-capacitance sensor islet operation pattern, analyze micro-grid system and fail the workload demand that meets and the ratio of total capacity requirement in the analysis and assessment phase.
3. microgrid energy management system according to claim 1, it is characterized in that, described power quality analysis at least comprises line voltage, mains by harmonics, grid voltage three-phase imbalance, the impact of reactive balance and the DC component of the grid-connected injection wherein one on the impact of micro-capacitance sensor.
4. microgrid energy management system according to claim 1, it is characterized in that, described economic feature of environmental protection analysis at least comprises the wherein one in economic benefit, environmental benefit and comprehensive benefit analysis thereof, and described comprehensive benefit is the summation of economic benefit and environmental benefit.
5. the microgrid energy management system according to any one of claim 1-4, is characterized in that, each unit of described micro-capacitance sensor is respectively micro battery, energy-storage units, load cell, switch element, protective relaying device, current transformer, transmission line.
6. the microgrid energy management system according to any one of claim 1-4, it is characterized in that, described state variable is node voltage amplitude and phase angle, and described control variables comprises the output terminal voltage of the meritorious of micro battery and idle power output and micro battery.
7. the microgrid energy management system according to any one of claim 1-4, is characterized in that, described optimum results comprises micro battery power, energy-storage units fills/put power, power is thrown/cut to the mutual power between micro-capacitance sensor and bulk power grid, controllable type load.
8. an energy management method for micro-grid, is characterized in that, it comprises the following steps:
Step 1, the collection each unit simulation amount of micro-capacitance sensor and switching value data, Weather information, phasor data, and the EMS data of connected electrical network; In conjunction with CIM, management micro-capacitance sensor Historic Section information, carries out data mining preliminary treatment, and the application for next step provides the model of integration, figure and parameter;
Step 2, model, figure and parameter in conjunction with described integration, carry out the micro-capacitance sensor state estimation based on hybrid measurement, ask for micro-capacitance sensor state variable; According to micro-capacitance sensor state variable and control variables, and in conjunction with the health status of each unit of micro-capacitance sensor, carry out risk analysis assessment and sensitivity analysis, predict potential fault, quantize the adjustment factor eliminating the out-of-limit fault of trend; By early warning and alarm module, danger, failure condition are warned with sound, light mode, and promptly takes corresponding precautionary measures or carry out emergency control; Described hybrid measurement comprises SCADA and measures and PMU measurement;
Step 3, information according to described micro-capacitance sensor state estimation, forecast and system cloud gray model analysis in conjunction with micro battery generating forecast, Load Forecasting, energy-storage units energy state, carry out the power flow management of micro-capacitance sensor;
Wherein, step 1 comprises:
Step 11, SCADA data acquisition and Monitor and Control, wherein, described SCADA data acquisition comprises the collection of each unit simulation amount of micro-capacitance sensor and switching value, Weather information, and described Monitor and Control comprises that equipment controls, measures, parameter regulates;
The synchronous acquisition of step 12, phasor data, described phasor data comprises the configuration node of phasor measuring set and voltage phasor, the electric current phasor of transmission line;
Relation between step 13, each unit of description micro-capacitance sensor and logical construction thereof, realize the information exchange between microgrid energy management system inside and different-energy management system and share;
Step 14, EMS data based on the data of described SCADA module acquires, the phasor data of PMU module acquires and connected electrical network, in conjunction with CIM, carry out data mining preliminary treatment, integrate micro-capacitance sensor Historic Section information, described micro-capacitance sensor Historic Section information is the set of the micro-capacitance sensor model structure of historical juncture, running status and electricity consumption condition information;
Described step 2 comprises:
Step 21, folding condition according to switch element, determine the electric connecting relation of each element in micro-grid system, and in conjunction with described micro-capacitance sensor Historic Section information, form network topological diagram;
Step 22, on the basis of Network topology, according to the data of described SCADA module acquires, and the phasor data of PMU module acquires, ask for electric network state variable;
The factor of random faule is caused in step 23, quantification micro-grid system, the consequence brought after estimating described random faule, set up can characterization system risk quantizating index and carry out calculating, analyzing, described in cause the factor of random faule to include but not limited to weather conditions, element state;
Step 24, utilize sensitivity calculations to draw to change with control variables and relation between the state variable that changes and control variables, instruct fast for providing the prevention and control of dangerous situation, simultaneously for the elimination of the out-of-limit fault of trend provides the adjustment foundation of quantification;
Described step 3 comprises:
Step 31, according to the historical load data in described micro-capacitance sensor Historic Section information, and consider weather forecast information, date category, carry out the prediction consuming electric energy;
The prediction of step 32, photovoltaic power and wind power prediction;
Step 33, predict the energy state of energy-storage units, so that analyze the power conversion of micro-capacitance sensor and storage capacity, described energy state comprises the energy of energy that energy-storage units stores and release;
Step 34, basis, from the micro-capacitance sensor state estimation information of described network analysis element, carry out the fail-safe analysis of micro-capacitance sensor, power quality analysis and economic feature of environmental protection analysis;
The forecast information of step 35, comprehensive micro battery generating forecast, Load Forecasting, energy-storage units energy state, on the basis of micro-grid system operating analysis and network analysis, the operational mode different for system and control objectives, export optimum results, provide concrete dispatch command to each unit; Described control objectives comprises reliability optimum, the economic feature of environmental protection is optimum.
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