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A method of estimating surface radioactivity concentrations of key anthropogenic radionuclides from NaI(Tl) pulse-height distribution observed at a monitoring station (MS) was discussed. In the estimation, a realistic assumption on geometric distribution of source and obstacles around the detector of the MS including the infiltration of radionuclides into the ground was used and the results were compared with ones with a commonly used assumption of a uniformly distributed plane source. The surface radioactivity concentration was determined by comparing the count rates at the full-energy peak ranges between observation and calculation with an electron-photon transport code EGS5. It was shown that the estimated absolute values of concentration differed by a factor of ∼1.5 depending on the assumption of infiltration depth. The estimated surface concentrations of (131)I, (134)Cs and (137)Cs were in good agreement with ones determined by the in situ measurements with an HPGe detector and the cumulative values of daily surface depositions.

A method of estimating surface radioactivity concentrations of key anthropogenic radionuclides from NaI(Tl) pulse-height distribution observed at a monitoring station (MS) was discussed. In the estimation, a realistic assumption on geometric distribution of source and obstacles around the detector of the MS including the infiltration of radionuclides into the ground was used and the results were compared with ones with a commonly used assumption of a uniformly distributed plane source. The surface radioactivity concentration was determined by comparing the count rates at the full-energy peak ranges between observation and calculation with an electron-photon transport code EGS5. It was shown that the estimated absolute values of concentration differed by a factor of ∼1.5 depending on the assumption of infiltration depth. The estimated surface concentrations of (131)I, (134)Cs and (137)Cs were in good agreement with ones determined by the in situ measurements with an HPGe detector and the cumulative values of daily surface depositions.

In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded.

In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded.

Studying the influence of the demand response and dynamic characteristics of the battery energy storage on the configuration and optimal operation of battery energy storage system (BESS) in the Wind-Photovoltaic (PV)-Energy Storage (ES) hybrid microgrid. A demand response model that is based on electricity price elasticity is established based on the time-of-use price. Take the capital-operating cost and direct economic benefit of the BESS and the loss of abandoned photovoltaic and wind power as the optimization objective, an optimal configuration method that considers the dynamic characteristics of the BESS and the maximum absorption of photovoltaic and wind power is proposed while using particle swarm optimization to solve. The results show that the configuration results considering the demand side response of the microgrid BESS can obtain better economy and reduce the storage capacity requirement, and the result shows that the efficiency of BESS relates to the load of the system, the distributed generation (DG) characteristics, and the dynamic characteristics of BESS. Meanwhile, the capacity and power of the energy storage configuration increase as the DG permeability increases due to the reverse load characteristic of the wind power.

Studying the influence of the demand response and dynamic characteristics of the battery energy storage on the configuration and optimal operation of battery energy storage system (BESS) in the Wind-Photovoltaic (PV)-Energy Storage (ES) hybrid microgrid. A demand response model that is based on electricity price elasticity is established based on the time-of-use price. Take the capital-operating cost and direct economic benefit of the BESS and the loss of abandoned photovoltaic and wind power as the optimization objective, an optimal configuration method that considers the dynamic characteristics of the BESS and the maximum absorption of photovoltaic and wind power is proposed while using particle swarm optimization to solve. The results show that the configuration results considering the demand side response of the microgrid BESS can obtain better economy and reduce the storage capacity requirement, and the result shows that the efficiency of BESS relates to the load of the system, the distributed generation (DG) characteristics, and the dynamic characteristics of BESS. Meanwhile, the capacity and power of the energy storage configuration increase as the DG permeability increases due to the reverse load characteristic of the wind power.

Abstract Numerical simulations with detailed homogeneous (gas phase) and heterogeneous (catalytic) chemistries of premixed hydrogen–oxygen mixture were performed inside a rectangular micro-combustor. The effects of catalytic walls on the homogeneous combustion were investigated via varying catalyst segment layouts and sizes. The interactions between heterogeneous and homogeneous reactions were discussed. It was shown that the heterogeneous reactions become weak when the catalyst disposition is shifted toward the outlet along the streamwise. The homogeneous combustion also becomes obviously weakened downstream behind the catalyst segmentation, except the exit. Moreover, with increasing catalyst segment size, the hydrogen conversion ratio increases and the mean outlet temperature reduces. The competition of the fresh fuel between the heterogeneous and homogeneous reactions result in the inhibition of heterogeneous reactions on homogeneous combustion. In summary, the heterogeneous reactions can obviously improve the combustion efficiency in a micro catalytic combustor. As expected, the effects of catalytic walls were more pronounced for the micro combustor systems.