Life Cycle Assessment,Estimation and Comparison of Greenhouse Gas Mitigation Potential of New Energy Power Generation in China

From the perspective of life cycle assessment （LCA）, the development, construction, and operation of all kinds of new energy power generation technologies release greenhouse gas （GHG） emissions. This sparks concerns about the lowcarbon nature of the new energy power generation technologies. Based on national and international literature review, this paper estimates and compares the GHG emission factors of traditional thermal power generation and new energy power generation technologies in China with the LCA approach. The GHG mitigation potential of new energy power generation technologies as substitution for traditional thermal power generation in China was evaluated, according to the objectives of new energy power generation of the national development planning. The results show that the GHG emission factors of new energy power generation axe much lower than that of traditional thermal power generation even with LCA accounting, and the GHG mitigation potential of new energy substitution is huge.

Renewable energy power generation projects started construction in Tibet

On March 19, the construction of a 10-MW photovoltaic power plant and a 1 000-kW new type geothermal power generation project were started by Guodian Longyuan Group in Yanbajing Town, Dangxiong County of Tibet.

Research of Thermal Energy Storage Technology in the Solar Thermodynamic Power

Recently, although renewable energy has a great development, primary source is still thermal power generation, which uses fossil fuel as the energy source. Supply and demand of fossil fuel are essential for social and economy development. However, development pattern that excessively relies on the natural source is impossible to provide a sustainable development way for us. As a result, we should combine renewable energy with new energy technology as the aim of economy. It means that it is urgent to exploit new energy. Meanwhile, the ratio of energy waste cannot be ignored. How to decrease energy waste is also significant. Construction sector costs a lot of energy, which is mainly used for heating and refrigeration. In the new energy generation technology, thermal energy can be transformed to electricity with combination of BIPV and thermal energy storage technology. Photovoltaic generation has a great progress in the building construction. As a result, the thermal energy storage technology becomes the key link in the production chain. In this paper, feasibility of applying phase-change material (PCM) in the thermal energy storage will be analyzed. And analysis results are provided with a relative mathematical model.

A review of cryogenic power generation cycles with liquefied natural gas cold energy utilization

Liquefied natural gas （LNG）, an increasingly widely applied clean fuel, releases a large number of cold energy in its regasification process. In the present paper, the existing power generation cycles utilizing LNG cold energy are introduced and summarized. The direction of cycle improvement can be divided into the key factors affecting basic power generation cycles and the structural enhancement of cycles utilizing LNG cold energy. The former includes the effects of LNG-side parameters, working fluids, and inlet and outlet thermodynamic parameters of equipment, while the latter is based on Rankine cycle, Brayton cycle, Kalina cycle and their compound cycles. In the present paper, the diversities of cryogenic power generation cycles utilizing LNG cold energy are discussed and analyzed. It is pointed out that further researches should focus on the selection and component matching of organic mixed working fluids and the combination of process simulation and experi- mental investigation, etc.

Coordinative Optimization of Hydro-photovoltaic-wind-battery Complementary Power Stations

The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry.Therefore,it is extremely urgent to transform energy production methods and vigorously develop renewable energy sources.It is therefore important to ensure the stability and operation of a large multi-energy complementary system,and provide theoretical support for the world’s largest single complementary demonstration project with hydro-wind-PV power-battery storage in Qinghai Province.Considering all the multiple power supply constraints,an optimization scheduling model is established with the objective of minimizing the volatility of output power.As particle swarm optimization(PSO)has a problem of premature convergence and slow convergence in the latter half,combined with niche technology in evolution,a niche particle swarm optimization(NPSO)is proposed to determine the optimal solution of the model.Finally,the multiple stations’coordinated operation is analyzed taking the example of 10 million kilowatt complementary power stations with hydropower,wind power,PV power,and battery storage in the Yellow River Company Hainan prefecture.The case verifies the rationality and feasibility of the model.It shows that complementary operations can improve the utilization rate of renewable energy and reduce the impact of wind and PV power’s volatility on the power grid.

Prediction-based dynamic routing intelligent algorithm in power optical communication network

New energy power generation equipment has the characteristics of diurnal, perturbative, seasonal, and periodic power generation, which makes new power optical communication network(POCN) more dynamic and changeable. This is directly reflected in the dynamics of the link risk and service importance of the POCN. In this paper, aiming at the problem of the dynamic importance of service in POCN, and the resulting power optical communication network reliability decline problem, a new energy POCN dynamic routing intelligence algorithm based on service importance prediction is proposed. Based on the short-term power generation of new energy power station, the importance of each service and the risk degree of each link are predicted. Link weights are dynamically adjusted, and k-shortest path(KSP) algorithm is used to calculate route results. When network resources are insufficient, low-importance services can give way to prevent a large number of high-importance services from being blocked. Simulation results show that compared with the traditional KSP algorithm, the prediction-based dynamic routing intelligent(P-DRI) algorithm can reduce the service blocking probability by 55.59%, and reduce the average importance of blocking services by 44.77% at the cost of about 6.17% of the calculation delay.