| According to the International Energy Agency estimates, in 2030 the global primary energy demand will reach 17.7 billion tons of oil equivalent, energy demand is huge. The fossil energy(coal, oil and natural gas) will continue to be the main source of primary energy. Due to the large number of the burning of fossil fuels, atmospheric concentrations of carbon dioxide and other greenhouse gases continue to increase, which has become one of the main causes of global warming and climate change. The world’s limited resources and the pollution of the environment is seriously restricting the development of the world economy and society. Optimizing energy structure, improving energy efficiency, development of new energy and renewable energy has become a major issue which all world is paying close attention to. From the energy security and energy strategy point of view, the solar energy is an ideal renewable green energy, solar power generation is an important way to solve the shortage of fossil fuels and reduce the pollution of the environment. Solar photovoltaic power generation convert solar energy directly into electrical energy by photovoltaic cells, which is an important way for the development of solar energy. At present, due to the photovoltaic cell low efficiency and high power cost of photovoltaic power generation system, it is difficult to quickly spread photovoltaic power generation system. At the same time, photovoltaic power generation system is low system integration level, poor reliability, high power consumption and the lack of effective monitoring measures. To solve these problems, we conducted the following research:1) Research on MPPT algorithm, to put forward a kind of partition of genetic MPPT algorithm. Because the output power of the PV array varies with the change of external environment, so MPPT circuit and the corresponding control method is widely used in the photovoltaic power generation system to improve the utilization efficiency of the PV array. Partition of genetic algorithm search space in all solution space and there is a parallel computer mechanism in the genetic algorithm, so it is easy to get the global optimal solution and overcome the shortcoming of easily falling into local minimum dilemma in the searching process. Crossover and mutation mechanism in genetic algorithm can overcome the defect of interference method which is easy to fall into the oscillation. Partition of genetic MPPT algorithm can meet the real-time control of MPPT, to ensure the normal operation of photovoltaic power generation system in different physical locations. Through simulation and experiment, this method can improve the dynamic and steady-state characteristics of the maximum power point tracking and this method compared with traditional method has higher accuracy and real-time control performance.2) Research on the solar auto-tracking method, to propose solar azimuth tracking method based the combination optical tracking and time tracking, design a two axis solar tracking device and double shaft sun position PSD sensor. In the time tracking mode, tracking device control system doesn’t distinguish the cloudy and the sunny and it starts tracking devices according to the procedures, which increase energy consumption. In the optical tracking method, there is a problem how a tracking device adapts to the weather changes and other issues. Optical tracking and time tracking combined can timely control and select the solar azimuth tracking mode according to the weather condition、adjust the operating mode of the system、reduce the energy consumption、eliminate the system error and improve the precision of tracking solar azimuth. A new dual axis tracking device convert the height angle and the azimuth angle parameters into two driving angle parameters. The new parameters drive PV array to move in the gimbal motion to track the sun. According to the method, a new solar azimuth tracking device is designed, which has high tracking precision, small tracking time interval, simple structure and low cost. Through the experiment, this method can improve the precision of the tracking device,reduce the system energy consumption and improve the power generation system.3) Research on online fault detection of photovoltaic array, to put forward a method of online fault detection of solar photovoltaic array. The artificial inspection is used in the fault detection method of photovoltaic arrays. Manual maintenance is time-consuming and inconvenient. The real-time remote monitoring, timely detection and repairing of the PV array can be realized by online fault detection. Online fault detection is divided into two steps, the first step is the use of new voltage, current detection method to find the fault module’s group; the second step is the detection performance parameters of the battery online and ultimately determine the fault location of the battery components. By experimental verification, this method can quickly and effectively detect PV array fault online.4) Research on self-tracking photovoltaic generating system reliability, to construct the fault tree of the tracking of photovoltaic power generation system; construct the state model of the photovoltaic automatic tracking power system, definite reliability index; calculate the photovoltaic generation system reliability of tracking. Photovoltaic power generation has the characteristics of intermittent and randomness. It is necessary to establish the appropriate model to evaluate the reliability of PV system for accurate measurement of photovoltaic power generation income to the grid and the objective evaluation of the value. Considering the photovoltaic power generation system structure and fault characteristics of the photovoltaic power generation system, four state reliability model of system reliability and the corresponding index system is established. System reliability is evaluated from the running time, the output power, the running state of the system. The results show that the model and the index system can reflect the operation situation, the photovoltaic power generation system output power level and fault conditions;reflect the running reliability of the system5) Research on Solar Photovoltaic Self-tracking Power Generation Monitoring System on Internet of Things, to construct self-tracking photovoltaic power monitoring system based on IOT architecture, design photovoltaic automatic tracking power monitoring experimental system based on the platform. The core of the Internet of things is the exchange of information between objects and objects, people and things. The basic characteristics of the Internet of things can be summarized as a comprehensive perception, reliable transmission and intelligent processing. Solar Photovoltaic Self-tracking Power Generation Monitoring System on Internet of Things consists of infrared image regular nondestructive testing subsystem and real-time online testing subsystem,(the perception layer); data transmission system(transport layer); evaluation and decision expert system(application layer). Designing and operation of photovoltaic power generation tracking monitoring experiment system to verify that the photovoltaic automatic tracking power monitoring system on IOT architecture can realize data interactive among the application layer, the perception layer and transport layer, realize remote decision-making, control and monitoring. The experimental system can monitor solar radiation, wind speed, PV array working condition, the working state of solar tracking device; can achieve MPPT tracking, solar tracking; can perform fault detection and reliability calculation. |
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