Advanced Materials Research Vol. 918

Abstract: Nowadays in a household PV generation system, it is generally connecting PV modules in series and then output to the power-conditioner. However, when PV modules are mismatched, it will lead to a wrong maximum power point tracking (MPPT) to all modules and a power decreasing of the whole system. Aiming at this problem, this paper presents the idea which improves the MPPT without changing the conventional power-conditioner, by adding a boost type DC-DC converter behind each module. Simulations of PSIM and experiments are taken to prove this theory. The result shows that, by this idea, the generated power of the conventional PV generation system can be greatly increased under the condition of mismatch.

Abstract: Electricity demand (load) forecasting has been recognizing as the key issue for achieving economic, reliable, and secure power system operation and planning. In the existing studies, two indentations are found in application level and methodology level, respectively. In the application level, the load forecasting for individual household is few. Most applications focus on large spatial region. In the methodology level, the importance of user daily schedule pattern is ignored in the development of load forecasting methods. In this study, a novel approach to model the load of individual household based on context information and daily schedule patterns is proposed. The daily schedule pattern types are induced from daily electricity consumption behaviors, and context features from several sources are collected and used to establish a rule set for classifying a given day into a specific behavior pattern type. Also, an electricity consumption volume prediction model is built for each behavior pattern type to predict the load of specific time point with in a day. A household very-short-term load forecasting problem which comes from Taiwan is implemented in this study. The results show that the proposed approach can get a better accuracy than other methods.

Abstract: Among the solving methods of probabilistic optimal power flow (P-OPF), Monte Carlo Simulation (MCS) combined with random sampling (RS) is widely used due to its high accuracy. In order to further improve that, this paper proposes a way of using Monte Carlo Simulation with Latin hypercube sampling (LHS) to calculate the consumption of generating cost under many random variables. Numerical results of IEEE 14-bus and IEEE 118-bus systems show that the Latin hypercube sampling method provides more accurate performance in dealing with POPF under the condition of a smaller sample size, comparing with random sampling method. Thus the Latin hypercube sampling method can replace the MCS with random sampling as the benchmark method of other algorithms.

Abstract: An efficient methodology of electro-thermal design of smart power semiconductor devices and ICs, based on the combined use of SPICE circuit analysis tool and software tools for 2D/3D thermal simulation of IC chip construction, is presented. The features of low, medium and high power elements, temperature sensors, IC chips simulation are considered.

Abstract: Renewable energy source (RES) enables us to diversify our energy supply. Renewable energy sources are getting more and more widespread, mainly due to the fact that they generate energy by keeping the environment clean. This increases our security of supply and improves European competitiveness creating new industries, jobs, economic growth and export opportunities, whilst also reducing our greenhouse gas emissions. This article proposes a simulation of a three-phase low voltage grid with power generation from photovoltaic sources. The proposed system consists of 192 photovoltaic (PV) panels distributed in 32 rows with each 12 PV panels.

Abstract: Recent studies suggest that in order to facilitate higher market and grid penetration of solar power, the users need accurate forecasts of generating power from photovoltaic (PV) plants on multiple time horizons. Despite the large number of forecasting methods, the comparison of results and evaluation of relative advantages between models has been evasive. The general purpose of the paper is to explore the way of performing accurate forecasts of generating power from renewable energy sources so that independent system operators can act consequently. Different aspects of radial basis functions (RBF) neural networks (NNs) are discussed and an illustration of the proposed predictor software interface is given.

Abstract: Fuel consumption, related to engine operation and performance, has always been emphasized in the modern design of heavy vehicles. For identifying the operational mechanism of a novel hydraulically actuated electronic unit injection (HEUI) system from the viewpoint of energy conversion, this study presents the estimation of a nonlinear autoregressive moving average with exogenous inputs (NARMAX) models. By this modeling approach, the correlation between injection pressure and fuel rate under normal operations is detected. When mapping the NARMAX models into the frequency domain, the frequency response functions (FRFs) representing the energy transfer mechanisms in the system can then be precisely obtained. Due to the high-order FRFs responsible for the non-linear coupling between the various input spectral components, the HEUI dynamics can be demonstrated as an energy resonance of 22.5 Hz.

Abstract: Based on LCA (Life Cycle Assessment) model, the paper analyzed the impacts of PHEVs (Plug in hybrid electric vehicle) on GHGs emissions in total life-cycle. To analyze and find out the most decisive life cycle phase with highest impacts, qualitative and quantitative analysis methods were adopted to analyze the specific impacts on specific life stage, such as the production phase, use and maintenance phase and disposal phase of vehicle life. The aim was to give a direction for the development of PHEVs (Plug in hybrid electric vehicle) in environmental protection field.

Abstract: For using vertical frozen working method as the reinforcement method at shield shaft, determination of the region of reinforcement, technology, as well as the evolution and distribution of temperature field of frozen soil curtain is the key problem. Aiming at shield launching project of Nanjing subway route-10 river tunnel, this paper applies finite element software to investigate the time series and distribution of temperature field. Nummerical results show that under the disigned frozen plan, the formation time of delivered circles in frozen wall, i.e., the required time for closing vertical frozen soil wall, is 7 days. After 30 days from frozen, vertical frozen forms a frozen soil wall of pressure load bearing for stopping water, with the thickness larger than 1.6m. Temperature in the area between frozen pipes at row B and tunnel face is lower than-26.67°C after 30 days from frozen. The distance between 0°C and-10°C isotherms and tunnel face is approximately 1.8m and 1.6m, respectively. 40 days after frozen, temperature in the area between frozen pipes at row B and tunnel face is still-26.67°C, but with larger area. The distance between tunnel face and 0°C and-10°C isotherms is approximately 2.1m and 1.8m, respectively. The numerical results provide theoretical data for future engineering designs that are simliar to the present study.

Abstract: Android platform data security mechanism and security vulnerabilities in android third party software were introduced. In order to eliminate the potential security threat, detection principle of traditional Trojan feature code was improved. A number of steps such as using c/s structure, establishing the Trojan family model on the server, receiving and checking the client's malicious, returning the results to the client, and the client adopting corresponding operation, as to ensure the information security of mobile phone user were researched.