Optimal planning of electric-vehicle charging stations in distribution systems

With the progressive exhaustion of fossil energy and the enhanced awareness of environmental protection, more attention is being paid to electric vehicles (EVs). Inappropriate siting and sizing of EV charging stations could have negative effects on the development of EVs, the layout of the city traffic network, and the convenience of EVs' drivers, and lead to an increase in network losses and a degradation in voltage profiles at some nodes. Given this background, the optimal sites of EV charging stations are first identified by a two-step screening method with environmental factors and service radius of EV charging stations considered. Then, a mathematical model for the optimal sizing of EV charging stations is developed with the minimization of total cost associated with EV charging stations to be planned as the objective function and solved by a modified primal-dual interior point algorithm (MPDIPA). Finally, simulation results of the IEEE 123-node test feeder have demonstrated that the developed model and method cannot only attain the reasonable planning scheme of EV charging stations, but also reduce the network loss and improve the voltage profile.

Optimal sitting and sizing of distributed generators considering plug-in electric vehicles

Some uncertainties such as the stochastic input/output power of a plug-in electric vehicle due to its stochastic charging and discharging schedule, that of a wind unit and that of a photovoltaic generation source, volatile fuel prices and future uncertain load growth, all together could lead to some risks in determining the optimal siting and sizing of distributed generators (DGs) in distributed systems. Given this background, under the chance constrained programming (CCP) framework, a new method is presented to handle these uncertainties in the optimal sitting and sizing problem of DGs. First, a mathematical model of CCP is developed with the minimization of DGs investment cost, operational cost and maintenance cost as well as the network loss cost as the objective, security limitations as constraints, the sitting and sizing of DGs as optimization variables. Then, a Monte Carolo simulation embedded genetic algorithm approach is developed to solve the developed CCP model. Finally, the IEEE 37-node test feeder is employed to verify the feasibility and effectiveness of the developed model and method. This work is supported by an Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) Project on Intelligent Grids Under the Energy Transformed Flagship, and Project from Jiangxi Power Company.

A series-connected photovoltaic distributed generator capable of enhancing power quality

Design of a series-connected photovoltaic generator (SPVG) capable of enhancing power quality is investigated. Analysis of the SPVG operations under disturbance conditions shows explicitly how achievable network voltage quality is affected by the SPVG injected power and its apparent power rating, and that voltage quality can be significantly improved even with a modest level of energy storage capacity incorporated in the SPVG. A control system for the SPVG is also proposed. Both simulation and laboratory tests confirm the efficacy of the distributed generator system.

Inhibition of the JAK2/STAT3 pathway in ovarian cancer results in the loss of cancer stem cell-like characteristics and a reduced tumor burden

Background Current treatment of ovarian cancer patients with chemotherapy leaves behind a residual tumor which results in recurrent ovarian cancer within a short time frame. We have previously demonstrated that a single short-term treatment of ovarian cancer cells with chemotherapy in vitro resulted in a cancer stem cell (CSC)-like enriched residual population which generated significantly greater tumor burden compared to the tumor burden generated by control untreated cells. In this report we looked at the mechanisms of the enrichment of CSC-like residual cells in response to paclitaxel treatment. Methods The mechanism of survival of paclitaxel-treated residual cells at a growth inhibitory concentration of 50% (GI50) was determined on isolated tumor cells from the ascites of recurrent ovarian cancer patients and HEY ovarian cancer cell line by in vitro assays and in a mouse xenograft model. Results Treatment of isolated tumor cells from the ascites of ovarian cancer patients and HEY ovarian cancer cell line with paclitaxel resulted in a CSC-like residual population which coincided with the activation of Janus activated kinase 2 (JAK2) and signal transducer and activation of transcription 3 (STAT3) pathway in paclitaxel surviving cells. Both paclitaxel-induced JAK2/STAT3 activation and CSC-like characteristics were inhibited by a low dose JAK2-specific small molecule inhibitor CYT387 (1 μM) in vitro. Subsequent, in vivo transplantation of paclitaxel and CYT387-treated HEY cells in mice resulted in a significantly reduced tumor burden compared to that seen with paclitaxel only-treated transplanted cells. In vitro analysis of tumor xenografts at protein and mRNA levels demonstrated a loss of CSC-like markers and CA125 expression in paclitaxel and CYT387-treated cell-derived xenografts, compared to paclitaxel only-treated cell-derived xenografts. These results were consistent with significantly reduced activation of JAK2 and STAT3 in paclitaxel and CYT387-treated cell-derived xenografts compared to paclitaxel only-treated cell derived xenografts. Conclusions This proof of principle study demonstrates that inhibition of the JAK2/STAT3 pathway by the addition of CYT387 suppresses the ‘stemness’ profile in chemotherapy-treated residual cells in vitro, which is replicated in vivo, leading to a reduced tumor burden. These findings have important implications for ovarian cancer patients who are treated with taxane and/or platinum-based therapies. Keywords: Ovarian carcinoma, Cancer stem cell, Metastasis, Ascites, Chemoresistance, Recurrence, JAK2/STAT3 pathway

Optimal allocation and sizing of capacitors to minimize the transmission line loss and to improve the voltage profile

To allocate and size capacitors in a distribution system, an optimization algorithm, called Discrete Particle Swarm Optimization (DPSO), is employed in this paper. The objective is to minimize the transmission line loss cost plus capacitors cost. During the optimization procedure, the bus voltage, the feeder current and the reactive power flowing back to the source side should be maintained within standard levels. To validate the proposed method, the semi-urban distribution system that is connected to bus 2 of the Roy Billinton Test System (RBTS) is used. This 37-bus distribution system has 22 loads being located in the secondary side of a distribution substation (33/11 kV). Reducing the transmission line loss in a standard system, in which the transmission line loss consists of only about 6.6 percent of total power, the capabilities of the proposed technique are seen to be validated.

An intelligent network control system for plug-in electric vehicles and the associate communication mechanism

The development of an intelligent plug-in electric vehicle (PEV) network is an important research topic in the smart grid environment. An intelligent PEV network enables a flexible control of PEV charging and discharging activities and hence PEVs can be utilized as ancillary service providers in the power system concerned. Given this background, an intelligent PEV network architecture is first developed, and followed by detailed designs of its application layers, including the charging and discharging controlling system, mobility and roaming management, as well as communication mechanisms associated. The presented architecture leverages the philosophy in mobile communication network buildup

Knowledge transfer through dual degree programs between Australian and Indonesian universities : a case study

While dual degree programs (DDPs) between Australian and Indonesian universities are expected to facilitate knowledge transfer (KT) between the partnering universities, little is known about how and what KT process taking place within DDP partnerships. Using an inter-organisational KT framework, this study investigated Indonesian universities’ rationales and outcomes of establishing DDPs and mechanisms facilitating knowledge transfer between Australian and Indonesian universities. Two Indonesian universities along with their common Australian partner university participated in this case study. Semi-structured interviews were conducted with 27 key university officers and pertinent university documents provided the main data. Both data sources were thematically analysed to identify emerging patterns. The findings suggest that Indonesian universities prioritised developing capacity to improve their international recognition more than the Australian partner. Consequently, the DDPs benefited the Indonesian universities through capacity development made possible by KT from the Australian DDP partners. KT processes occurred in DDP partnerships, particularly through curriculum collaboration, but they were more limited for the managerial area. Factors enabling the KT included both technology-aided and face-to-face communication, intention to acquire knowledge from the partners, capitalising on the unequal power relations to advance KT opportunities, and knowledge management system. The findings of this study suggest the importance of prioritising capacity development in DDP partnerships to enable KT, executing the KT stages to ensure institutionalisation of acquired knowledge into the university’s systems and policies, and maintaining financial sustainability of the DDPs to reach mutually beneficial outcomes between Australian and Indonesian universities.