New generation traction power supply system and its key technologies for electrified railways

Unlike the traditional traction power supply system which enables the electrified railway traction sub- station to be connected to power grid in a way of phase rotation, a new generation traction power supply system without phase splits is proposed in this paper. Three key techniques used in this system have been discussed. First, a combined co-phase traction power supply system is applied at traction substations for compensating negative sequence current and eliminating phase splits at exits of substations; design method and procedure for this system are presented. Second, a new bilateral traction power supply technology is proposed to eliminate the phase split at section post and reduce the influence of equalizing current on the power grid. Meanwhile, power factor should be adjusted to ensure a proper voltage level of the traction network. Third, a seg- mental power supply technology of traction network is used to divide the power supply arms into several segments, and the synchronous measurement and control technology is applied to diagnose faults and their locations quickly and accurately. Thus, the fault impact can be limited to a min- imum degree. In addition, the economy and reliability of the new generation traction power supply system are analyzed.

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.

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.

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.