Liu Liqun

An improved perturbation and observation MPPT method of photovoltaic generate system

An efficient Maximum Power Point Tracking (MPPT) algorithm is important to increase the output efficiency of a photovoltaic (PV) generate system. The conventional perturbation and observation (PO) MPPT algorithm is impossible to quickly acquire the maximum power point (MPP), and the tracking course is very difficulty under veil weather conditions, and the essential reason is not known the actual values of the n and Io. It is well-known that the different solar cells have different n and Io. Theoretical and simulative results show that a piece of solar cell has same photocurrent under different n and Io conditions. A new combined perturb and observe (PO) method is described in order to acquire the actual n and I. Then an improved PO maximum power point tracking method is described which based on the actual n and Io, and the tracking bound is reduced, and the tracking speed is rapid to compare with the conventional PO method. Furthermore, it is simple and can be easily implemented in digital signal processor (DSP). The simulation results verified the correctness and validity of MPPT method.

The MPPT Control Method by Using BP Neural Networks in PV Generating System

An efficiency method of Maximum Power Point Tracking (MPPT) is extremely important to improve the output characteristic of photovoltaic (PV) power generation system and reduce the cost of the system. The nonlinear and time-varying output characteristics of PV in the changing weather cause the difficult MPPT process. Neural networks algorithm is suitable for solving the nonlinear relation, and the result of comparing with the traditional disturbance observation shows that neural networks has better MPPT characteristics. The MPPT controller based on Back Propagation (BP) networks play an effective role to improve the efficiency and reduce the output vibration of PV power system.

Green and sustainable City will become the development objective of China’s Low Carbon City in future

Environmental pollution and greenhouse gas emissions are becoming significant environmental issues in China, thus the sustainable development and revival of the country is impossible using the conventional path of encouraging economic growth at the expense of the environment. In response to the global warming, the prices of the traditional energy rise considerably, and a series of environmental problems, China must improve its own mode of economic development. Hundreds of Chinese cities have billions of square meters of buildings and most industry and the annual energy demand is an astronomical figure. China’s government is facing increasing pressure in the low carbon international backdrop, and the low carbon city becomes the inevitable developmental direction of Chinese city in the foreseeable future. The description is first centered on energy structure/energy consumption per unit/urbanized status, and urban energy consumption status, and then concerned with the efforts and measures of Chinese government, to realize the energy saving. Finally, we present the developmental prospect and barriers and the promotion measures related to the low carbon city under the government policy, financial incentives and funding supports, etc.

NN-SMC MPPT Method for PV Generating System

An efficient Maximum Power Point Tracking (MPPT) method is extremely important to improve the output efficiency and electrical energy quality of a photovoltaic (PV) generating system. The MPPT course is very difficult due to the nonlinear and time-varying output characteristic of a PV system. SMC (sliding mode control) is used to track maximum power point (MPP) of PV system, and the results represent that the SMC have better tracking characteristic as compare with the conventional perturb and observe (PO) method. The RBF neural network is used to improve the SMC in order to increase the electrical energy quality and reduce the output vibration. The simulation results show the reliability of the suggested method, and the output and dynamic characteristics of PV system are significantly improved.