1224results about "Fuel cell control" patented technology

The invention discloses a hydrogen fuel cell vehicle ultralow temperature cold start thermal management system, and relates to the technical field of hydrogen fuel cell vehicle thermal management, the hydrogen fuel cell vehicle ultralow temperature cold start thermal management system comprises a thermal management platform, the thermal management platform is in communication connection with the following modules: a temperature monitoring and predicting module, and the temperature prediction module is used for monitoring the temperature of key parts in the hydrogen fuel cell by using the temperature sensor and predicting the change trend of the temperature in the fuel cell in combination with the temperature prediction model. By utilizing the high-precision temperature sensor and the long-short-term memory network model, the internal temperature change trend of the fuel cell is pre-judged in advance, the heating power is dynamically adjusted, it is ensured that the temperature of the cell is rapidly increased to the proper working temperature in the ultralow-temperature environment, starting difficulty caused by local supercooling is avoided, the low-temperature starting time is remarkably shortened, and the starting efficiency is improved. The reliability and the stability of the system in an extreme environment are improved, and the normal operation of the hydrogen fuel cell vehicle in a cold region is guaranteed.

The invention discloses a fuel cell hydrogen circulation cooling integrated system, and relates to the technical field of fuel cells, the fuel cell hydrogen circulation cooling integrated system comprises a hydrogen circulation cooling management center, the hydrogen circulation cooling management center is in communication connection with the following modules: a multi-source state sensing module, which is used for collecting multi-dimensional state data of a hydrogen circulation-cooling system in real time, extracting state characteristics, and sending the state characteristics to a control module; and forming a state feature sequence table. The multi-dimensional state data of the hydrogen circulation-cooling system is collected, the dynamic cooperative control strategy of the reinforcement learning decision module is combined, the precision and stability of temperature control are remarkably improved, the Markov decision process model is used for predicting the instantaneous heat production change caused by load sudden change, and the stability of the system is improved. And through combined adjustment of hydrogen circulation and a cooling system, temperature fluctuation is rapidly restrained, compared with traditional PID control, the temperature overshoot is reduced under the dynamic working condition, it is ensured that the galvanic pile works within the optimal temperature range all the time, the service life of the galvanic pile is prolonged, and the energy conversion efficiency is improved.

The invention discloses an intelligent energy scheduling method and system for a flow battery, and relates to the technical field of flow batteries, and the method comprises the following steps: collecting energy operation parameters of the flow battery in real time, and dynamically estimating an electrolyte state to obtain multiple pieces of energy state information; a target to be dispatched is set, and a fuzzy control strategy is formulated through retrograde multi-target optimization; executing a fuzzy control strategy to generate a regulation and control signal set and scheduling; and finally, according to a scheduling result, performing reverse tracing to optimize a fuzzy control strategy, and updating a regulation signal set to obtain a multi-stage regulation instruction to perform intelligent scheduling on the energy of the flow battery. The method solves the technical problems of low matching degree between a scheduling strategy and an actual demand, large power loss and fast battery life attenuation caused by difficulty in accurately capturing an energy state in real time in a traditional flow battery scheduling method, and achieves the purposes of intelligent flow battery energy scheduling, power loss reduction, battery life prolonging and energy conservation. And the matching degree between the scheduling and the actual demand is improved.

The invention discloses a gas-heat-electricity balance management and control method and system for a kilowatt-level SOFC (solid oxide fuel cell) cogeneration system, and belongs to the field of solid oxide fuel cells. The method comprises the following steps: setting initial operation parameters according to structure parameters and design working conditions of an SOFC electric pile, a heat exchanger, a reformer and a catalytic burner; a module start-stop coordination instruction is generated through the integrated controller, and temperature and pressure changes of all the modules in the start-stop process are controlled; system operation data are monitored in real time through a sensor, real-time diagnosis is conducted through a multi-dimensional data fusion algorithm, and abnormal states such as over-burning, over-air and temperature runaway are recognized; and according to the diagnosis result, the fuel flow, the air flow, the heat exchange power and the like are adjusted through a multivariable dynamic regulation and control strategy, so that reactor temperature fluctuation is controlled, and a temperature runaway early warning signal is generated. According to the method, the overall stability and efficiency of the SOFC combined heat and power system are improved by optimizing gas-heat-power balance management and control.

The invention discloses a fuel cell vehicle thermal management system and a construction method thereof, and the fuel cell vehicle thermal management system comprises a thermodynamic modeling module, a double-layer fuzzy sliding mode controller, an actuator cooperative control module, a working condition adaptive module and a fault protection module. According to the thermal management system of the fuel cell vehicle and the construction method of the thermal management system, the dynamic thermodynamic model is established, and the double-layer fuzzy sliding mode controller and the actuator cooperative control module are designed, so that millisecond-level high-precision tracking of the temperature of the electric pile and online real-time compensation of unknown disturbance are realized; meanwhile, stable operation of the system in the whole working condition domain range can be ensured through the working condition self-adaption module and the fault protection module, and the system has the advantages of being high in control precision, high in anti-interference capacity and good in system reliability.

The invention discloses a multi-dimensional multi-physics field coupling analysis platform of a hydrogen fuel cell based on artificial intelligence, and relates to the technical field of hydrogen fuel cells, the platform comprises a user interaction interface module, a multi-physics field model construction module, a data acquisition and preprocessing module, an integration module and an analysis and result output module; an electrochemical reaction model, a temperature field model and a gas and liquid flow model are respectively built through a multi-physical field model building module, the coupling strength among different physical fields is quantified, and the electrochemical reaction model, the temperature field model and the gas and liquid flow model are integrated into a multi-physical field model; physical action parameters such as electrochemical reaction rate, temperature value and the like are associated with time change, spatial distribution and fault conditions, so that the platform can simulate the multi-physical field coupling effect of the hydrogen fuel cell under complex working conditions, and the performance of the fuel cell is analyzed; and a reliable basis is provided for the geometric structure, material selection and operation condition optimization of the fuel cell.

The invention relates to an electrolytic hydrogen production and fuel cell waste heat gradient utilization system and method based on an organic Rankine cycle, and belongs to the field of new energy. The system comprises a wind power generation unit, a photovoltaic power generation unit, a storage battery energy storage system, an electrolytic hydrogen production device, a hydrogen storage system, a fuel cell power generation unit, a waste heat utilization unit and an organic Rankine cycle device, and can be used for realizing multi-element consumption and gradient utilization of renewable energy sources. The method specifically comprises the following steps: establishing equipment models in a system, wherein an electrolytic bath considers five states of shutdown, cold start, standby, hot start and standby; on the basis of a mixed integer linear programming method, operation constraints of all equipment, renewable energy output prediction and electricity, heat and hydrogen load requirements are integrated, an optimization scheduling model meeting the electricity, heat and hydrogen load requirements and economical efficiency of the system is constructed, output of all the equipment is coordinated, and finally the optimization targets of maximizing the economical efficiency of the system and meeting the electricity, heat and hydrogen load requirements of the system are achieved.

The invention relates to the technical field of fuel cells, in particular to a method and system for accurately controlling the hydrogen stoichiometric ratio of a fuel cell, and the method comprises the steps: firstly, obtaining a quantitative anode health state value through a fusion calculation model by collecting load current, anode inlet and outlet pressure, temperature, high-frequency resistance and other multi-source signals in real time; a feed-forward model based on a load current change rate predicts sudden change of hydrogen demand, and an optimal hydrogen flow instruction is jointly generated in combination with output of a PID controller which adaptively adjusts parameters according to a health state value. According to the method, the integrated diagnosis parameter, namely the anode health state value, is created, so that the internal state of the fuel cell can be accurately perceived and prospectively judged. Through deep fusion of multi-source heterogeneous information such as high-frequency resistance, anode pressure difference, current and temperature, a comprehensive index capable of comprehensively and quantitatively reflecting anode water content, gas concentration and runner smoothness is generated.

The invention relates to the technical field of fuel cell control, and discloses a control method of a hydrogen fuel system controller, which comprises the following steps: in response to a system shutdown instruction, controlling a DC / DC converter to maintain operation and request a preset scavenging current, and consuming residual reaction gas in a flow channel and a pipeline by using an electrochemical power generation reaction in an electric pile; meanwhile, hydrogen-cut air-down operation is executed, and the average single voltage of the electric pile is collected in real time; when it is monitored that the average monomer voltage is reduced to be below a preset anti-corrosion safety threshold value, the DC / DC converter is controlled to be disconnected, and mechanical purging is started. A time sequence interlocking mechanism of electrochemical energy depletion and mechanical purging is established, a high-potential retention path in the shutdown process is blocked from the physical and chemical source, and the safety of the shutdown is improved. Reverse polarity corrosion caused by a hydrogen-air interface effect is avoided, and the service life of the galvanic pile is prolonged.

The invention relates to the technical field of vehicle-mounted hydrogen fuel cells, and particularly provides a vehicle-mounted hydrogen fuel cell pack uncertainty quantification method and system, and the method comprises the steps: receiving an uncertainty quantification instruction, confirming an analysis environment, and constructing a running state association diagram; retrieving initial uncertainty influence factors based on an environment data set acquired by an external environment monitoring end, and confirming a target management strategy; updating the operation state association diagram and obtaining a fuel cell performance prediction sequence; key updating nodes are extracted to generate updating results, and dynamic quantization is achieved. According to the method, the operation data and the environment data are combined, the uncertainty management strategy is dynamically optimized, and the intelligent analysis and prediction capability of the operation state of the fuel cell stack is remarkably improved, so that the accuracy and efficiency of uncertainty management are enhanced.

The invention relates to the technical field of fuel cell monitoring and health management, and discloses an intelligent cooperative high-power proton exchange membrane fuel cell life prediction and fault diagnosis method and system, and the method comprises the following steps: S1, collecting multi-dimensional data of a stack key region in real time through a distributed sensing array; s2, removing noise and abnormal values of the collected data, and carrying out feature extraction; s3, constructing a dual-model collaborative prediction framework; s4, inputting the real-time features into the double models; s5, generating a maintenance strategy and early warning; according to the invention, special hardware accelerators such as a graphic processing unit or a field-programmable gate array are integrated on the edge computing module, so that the processing speed and efficiency of high-frequency and multi-source sensor data at a local end are remarkably improved; a distributed computing framework is adopted in a cloud analysis module to process mass feature data transmitted by an edge end, so that the capability and scale of the system for performing deep analysis on the health state of the fuel cell, accurately predicting the remaining service life and quickly tracing the fault are enhanced.

The subject matter described herein generally relates to look ahead energy management and control systems and methods for detecting, incorporating, and leveraging look ahead technology data to improve the performance, durability, and life of fuel cell systems.

The invention discloses a relaxation time distribution-based hydrogen fuel cell equivalent circuit model establishment method, and belongs to the technical field of hydrogen fuel cells. The method comprises the following steps: acquiring full-band impedance data of the hydrogen fuel cell; performing relaxation time distribution analysis on the full-band impedance data to obtain a relaxation time relation spectrogram; identifying and constructing an initial equivalent circuit model based on characteristic peaks of different frequency bands in the relation spectrogram; the characteristic peaks at different frequency bands are used for representing different electrochemical characteristic processes of the hydrogen fuel cell; and according to the full-band impedance data and the initial equivalent circuit model, performing model parameter adjustment, and based on the adjusted model parameters, obtaining an equivalent circuit model constructed for the hydrogen fuel cell. According to the method, the high-precision and reasonable equivalent circuit model can be constructed.

A coordinated optimization method and system for a hydrogen fuel cell vehicle, a device, and a medium. The method includes: determining a target output voltage and a target output current corresponding to a stack in a hydrogen fuel cell vehicle; determining a sub-stack efficiency score corresponding to one of sub-stacks, and determining a sub-stack stability score corresponding to the sub-stack; obtaining a comprehensive score of the sub-stack efficiency score and the sub-stack stability score, and determining a primary stack and a secondary stack from the sub-stacks according to a comprehensive score result; generating, according to the target output voltage and the target output current, a primary stack output parameter corresponding to the primary stack and a secondary stack output parameter corresponding to the secondary stack; and dynamically adjusting an operating state of the primary stack, and dynamically adjusting an operating state of the secondary stack.

The present disclosure provides a prediction method of electrochemical and mechanical performances of a Solid Oxide Fuel Cell (SOFC) in a cold-hot cycle, and belongs to the technical field of SOFCs. In the present disclosure, a cold-hot cycle test is performed on SOFC pile, a polarization curve and an electrochemical impedance spectroscopy are measured by an electrochemical workstation, and contributions of different electrode reaction processes to voltage attenuation are analyzed quantitatively; the mechanical performance (bending strength, elastic modulus and hardness) after different numbers of cold-hot cycle services is tested, and based on change of Ni particles, the electrochemical performance and the mechanical performance of the SOFC pile are quantitatively associated; an attenuation coupling relationship of the electrochemical performance and the mechanical performance of the SOFC pile is disclosed and an attenuation theory model of the electrochemical performance and the mechanical performance of the SOFC pile is built. In this way, a change law of the electrochemical performance and the mechanical performance of the SOFC pile after different numbers of cold-hot cycles and a cold-hot cycle service life of the SOFC pile can be accurately predicted, which is of great significance to improve the thermal shock resistance of the cold-hot cycles of the SOFC pile, so as to promote SOFC commercialization applications.

The utility model relates to the technical field of vanadium redox flow batteries, in particular to a large all-vanadium redox flow energy storage power station SOC balance recovery control system which comprises at least two redox flow battery modules, an energy storage converter and a battery management system. The flow battery module comprises an electric pile group, a positive electrode electrolyte storage tank, a negative electrode electrolyte storage tank, a variable frequency pump and SOC sensors connected in parallel to two ends of the electric pile group. During working, the SOC of each battery module is evaluated in real time through a battery management system (BMS) control system; when the BMS system monitors that the SOC difference value between the electric pile groups is too large, the SOC difference value is generally 5%. The BMS system adjusts the flow of the electrolyte flowing through the galvanic pile groups by controlling the frequency of the variable frequency pumps of the galvanic pile groups, so that the internal resistance of the galvanic pile groups is adjusted, and the charging and discharging power on each galvanic pile group is adjusted.

The invention relates to a simulation model construction method based on a PEMFC electric pile and a storage medium, and the method comprises the steps: carrying out the dimension reduction modeling of an MEA part and a BP part of a real battery, and obtaining a PEMFC dimension reduction model; an equivalent battery model is constructed based on the real battery, the equivalent battery model comprises a plurality of equivalent batteries, and the equivalent batteries are equivalent to the real battery and other most porous medium areas and are suitable for participating in the temperature generation and transmission process and the gas flowing and distribution process; and constructing a simulation model based on the PEMFC stack based on the PEMFC dimensionality reduction model and the equivalent battery model. By constructing the PEMFC dimension reduction model, the structure of part of batteries in the electric pile is simplified, the complexity of model solution is reduced, and the economic and calculation cost of the simulation process is greatly saved.

The invention relates to the technical field of cell regulation and control, in particular to a fuel cell gas flow field optimization control system and method based on automatic regulation and control. The method comprises the following steps: deploying a gas flow sensor, a pressure sensor, a temperature sensor and a humidity sensor in a fuel cell, and monitoring gas flow data, gas pressure data, gas temperature data and gas humidity data in real time; gas flow channel structure parameters are obtained, gas distribution flow field coupling simulation and reaction output load evaluation are carried out, and a gas reaction output power load is obtained; and carrying out battery reaction activity influence analysis and gas reaction abnormity quantification on the corresponding reaction distribution area in the fuel battery to obtain a gas reaction distribution abnormity degree, and carrying out reaction distribution non-uniformity determination and gas flow optimization control so as to execute corresponding reaction distribution non-uniformity gas flow control work. According to the invention, uniform distribution of gas in the fuel cell can be ensured, and the performance and stability of the cell are continuously improved.

The invention discloses a PEMFC (proton exchange membrane fuel cell)-ORC (organic Rankine cycle)-TEG (thermoelectric generator) coupling-based waste heat utilization system and a coupling method. A PEMFC module, an ORC module and a TEG module are coupled; the system comprises a fuel cell, a TEG assembly, a condenser, a delivery pump, a pressure pump, a cooling water storage tank, an evaporator, an expansion machine, a filter, a humidifier, an ejector, a compressor and an electromagnetic valve. Heat carried by cooling water in the PEMFC cooling system is used as a main energy source for waste heat recovery. As the heat taken away by the cooling water is far greater than the directly discharged waste heat, the cooling water has higher enthalpy value and excellent heat recovery potential. By constructing a reasonable heat recovery path and a heat exchange network, the waste heat gradient utilization efficiency can be remarkably improved, and the higher primary energy utilization rate is achieved. And efficient recovery and gradient utilization of the waste heat of the PEMFC are realized.

The invention relates to the field of hydrogen energy storage and supply, and discloses a heat storage system for a hydrogen supply and storage system, comprising: a storage and supply integrated water tank for storing waste heat generated by a fuel cell generator set; the waste heat recovery side water pump is used for conveying waste heat of the fuel cell generator set to the storage and supply integrated water tank; the user water supply side water pump is used for extracting heat from the storage and supply integrated water tank and supplying the heat to rear-end users; the pipeline and valve group is used for connecting all the parts and adjusting the flowing direction and flow of heat; the gradient utilization module is used for graded utilization of waste heat generated in the hydrogen supply and storage process; and the collaborative conversion module is used for carrying out collaborative conversion and storage among the energy sources. An energy demand is predicted by applying a deep hydrogen energy storage and supply Q hydrogen energy storage and supply network algorithm, an optimization model is constructed in combination with equipment operation constraints, equipment is accurately regulated and controlled, and the energy demands are respectively used for power generation, refrigeration, heating and industrial production according to waste heat temperature differences, so that flexible distribution of waste heat is realized.

The invention relates to the field of fuel cell engines, in particular to a fuel cell bypass flow determining method and device, a storage medium and a vehicle, and the method comprises the steps that state data of a bypass valve of a fuel cell are collected, and the state data comprise the opening degree, the temperature and the pressure of the bypass valve; inputting the opening degree and the pressure of the bypass valve into the neural network prediction model to obtain the predicted standard condition flow of the bypass valve; the neural network prediction model is obtained based on historical sample data training of the bypass valve; calculating a correction factor according to the temperature and the pressure of the bypass valve; and according to the standard condition flow of the bypass valve and the correction factor, a fuel cell bypass flow predicted value is obtained through calculation. Through the combination of the neural network model and the correction factor, the precision, efficiency and cost are considered, and the limitations of the traditional MAP method in the aspects of precision, memory, data utilization and the like are solved.

The invention discloses an MPC-SP-based all-vanadium redox flow battery constant-power charging and discharging control method, which is applied to an energy storage control system composed of an MPC-SP controller, a PCS and an all-vanadium redox flow battery, and is characterized in that the controller dynamically and accurately adjusts the power output to the battery based on preset SOC interval division, and the power output to the battery is increased along with the increase of the actual SOC value of the battery. The power is increased in stages. Meanwhile, the controller pays attention to the voltage Ud of the battery end all the time, and when the Ud reaches a voltage limiting value, the constant voltage mode is switched, so that the battery is effectively prevented from being damaged due to overhigh voltage. The state-based dynamic power management is much safer, more flexible and more intelligent than traditional fixed constant power control. According to the invention, the change rate of current in the charge-discharge process of the all-vanadium redox flow battery can be reduced, the service life of the battery is prolonged, and the safety is guaranteed.

The invention provides a marine fuel leakage control method and system, and belongs to the technical field of ship engineering.The method comprises the steps that multi-physics field data are collected, and the multi-physics field data comprise marine fuel concentration data, temperature data and pressure data; performing feature extraction on the marine fuel concentration data, the temperature data and the pressure data to obtain marine fuel leakage feature parameters; the marine fuel leakage characteristic parameters are input into a marine fuel leakage early warning model for prediction, and the marine fuel leakage probability and the marine fuel leakage position are obtained; and generating a marine fuel leakage control instruction based on the marine fuel leakage probability and / or the marine fuel leakage position. According to the method, the leakage probability and position of the marine fuel are accurately predicted, and the safety of ships and personnel is guaranteed.

The invention belongs to the technical field of thermal management, and particularly relates to a dynamic thermal management method and system for a cascade thermal coupling control system. The method comprises the following steps: judging the running state of the current cascade thermal coupling control system; based on the operation state, obtaining operation parameters of the cascade thermal coupling control system in real time; adjusting the heat flow path according to the operation parameters to obtain an actual heat flow value; obtaining a heat flow prediction value by using the heat flow prediction model, and comparing the heat flow prediction value with an actual heat flow value to obtain a heat flow difference value; and adjusting operation parameters of the cascade thermal coupling control system according to the heat flow difference value, and controlling the dynamic heat flow of the cascade thermal coupling control system. According to the invention, the objective function is constructed based on the LSTM neural network, and the state of the phase change material can be adjusted in real time in cooperation with the phase change progress-resistance value mapping model, so that the distribution of the heat flow is realized, and the dynamic management of the cascade thermal coupling control system is completed.

The invention discloses a supercharged SOFC / GT combined cycle system and a starting method, and relates to an SOFC / GT combined cycle system and a starting method. The invention aims to solve the problem that the requirements of short starting time and high energy utilization rate cannot be met in the prior art. The system comprises a gas compressor, the gas compressor is coaxially connected with a turbine and a permanent magnet synchronous motor, an outlet of the gas compressor is connected with an inlet of a first flow divider, one outlet of the first flow divider is connected with a first battery assembly, and the other outlet of the first flow divider is connected with an inlet of a second flow divider; one outlet of the second shunt is connected with a heat exchanger assembly, the other outlet of the second shunt is connected with a combustion chamber, an outlet of the combustion chamber is connected with a turbine, an outlet of the turbine is connected with a heat exchange assembly, the heat exchange assembly is connected with the combustion chamber, the permanent magnet synchronous motor is connected with a power grid bus, and the power grid bus is connected with a second battery assembly. The first battery assembly is connected with the power grid bus. The invention belongs to the technical field of energy power equipment.

The present invention relates to a fuel cell system (100) for regulating and / or controlling a fuel utilization (FU sys ) of the fuel cell system (100) and / or a fuel utilization (FU Stk ) of a fuel cell unit (101) of the fuel cell system (100). Furthermore, the invention relates to a corresponding method for operating a fuel cell system (100), a computer program product, a computer-readable data carrier, a control unit (FCCU), and a system (200).

The invention relates to the technical field of fuel cells, and provides a method and a device for optimizing operation conditions of a proton exchange membrane fuel cell. The method comprises the following steps: simulating the proton exchange membrane fuel cell according to a local dimension reduction single cell model and initial operation conditions of the proton exchange membrane fuel cell to obtain initial effective output power; sequentially increasing each initial parameter value under the initial operation condition to obtain a target operation condition; simulating the proton exchange membrane fuel cell again according to the target operation condition and the local dimensionality reduction single cell model to obtain the target saturation of liquid water of the cathode catalyst layer and the target effective output power; and obtaining a performance evaluation value corresponding to the target operation condition according to the initial effective output power, the target effective output power and the target saturation degree of the liquid water of the cathode catalyst layer, so as to determine the target operation condition corresponding to the performance evaluation value as the optimal operation condition. By adopting the method, the precision of the performance evaluation value can be improved, and the optimization effect of the operation condition is further improved.

The invention discloses a PEMFC life prediction method based on G-WD and an optimized TCN-Transformer model, and relates to the technical field of proton exchange membrane fuel cells. According to the method, physical parameters with strong correlation, which are obtained by a Spearman correlation analysis method, are combined with time domain, frequency domain, entropy and wavelet features in data extracted per hour, and reconstruction data after wavelet decomposition is optimized are combined as multi-feature input; according to the PEMFC life prediction method, the TCN-Transform time sequence model has more dimensional features and can be learned and trained, the prediction performance is enhanced by using the optimized TCN-Transform model, and the PEMFC life prediction method is provided.

The invention specifically discloses an all-vanadium redox flow battery multi-target operation optimization control method based on a particle swarm algorithm, and relates to the technical field of all-vanadium redox flow battery energy storage system control. The method comprises the following steps: firstly, collecting and preprocessing real-time operation data of a VRB system; constructing a multi-objective optimization function including charging time, input / output energy and pump energy consumption in a charging and discharging mode; taking the charge-discharge current density and the electrolyte flow as decision variables, taking the temperature, the voltage and the SOC value as constraint conditions, and carrying out optimization solving through a particle swarm optimization algorithm to obtain optimal parameters; and finally, realizing full-process automatic closed-loop control by combining data acquisition, function calculation, parameter adjustment and simulation feedback. According to the method, through multi-target dynamic optimization, decision variable and constraint condition and closed-loop adaptive control, collaborative optimization of shortening the charging time of the all-vanadium redox flow battery, improving the system efficiency and reducing the pump energy consumption is realized, and the operation safety, stability and complex scene adaptability of the system are enhanced.

An electric power supply system includes: a first electric power supply part that utilizes a commercial electric power supply source; a second electric power supply part that utilizes a vehicle battery or other supply source; a third electric power supply part that utilizes a fuel cell; a fourth electric power supply part that utilizes photovoltaic electric power generation; a first electric power supply line for supplying electric power to an important appliance group; a second electric power supply line for supplying electric power to a general appliance group; and a distribution board. The distribution board includes: a first switch to switch over the first electric power supply part and the second electric power supply part at an input; a second switch to switch over the third electric power supply part and an output of the first switch at an input, the second switch having an output connected to the first electric power supply line; and a third switch to switch over the fourth electric power supply part and the output of the first switch at an input, the third switch having an output connected to the second electric power supply line.