Prasanta Ghosh

Optimizing Electric Vehicle Charging With Energy Storage in the Electricity Market

The Information and Communication Technologies (ICT) that are currently under development for future smart grid systems can enable load aggregators to have bidirectional communications with both the grid and Electric Vehicles (EVs) to obtain real-time price and load information, and to adjust EV charging schedules in real time. In addition, Energy Storage (ES) can be utilized by the aggregator to mitigate the impact of uncertainty and inaccurate prediction. In this paper, we study a problem of scheduling EV charging with ES from an electricity market perspective with joint consideration for the aggregator energy trading in the day-ahead and real-time markets. We present a Mixed Integer Linear Programming (MILP) model to provide optimal solutions as well as a simple polynomial-time heuristic algorithm based on LP rounding. In addition, we present a communication protocol for interactions among the aggregator, the ES, the power grid, and EVs, and demonstrate how to integrate the proposed scheduling approach in real-time charging operations. Extensive simulation results based on real electricity price and load data have been presented to justify the effectiveness of the proposed approach and to show how several key parameters affect its performance.

Numerical calculation of effective permittivity of lossless dielectric mixtures using boundary integral method

The electrostatic environment in a lossless composite structure made of three dielectrics and two dividing closed and disjoined surfaces has been determined, using appropriate surface integrals on these interfaces. These integral equations are transformed to approximate matrix equations and then are solved numerically. The electrostatic potential distribution, dipole moment and the effective permittivity of different composite structures are calculated. >

Coordinated usage of distributed sources for energy cost saving in micro-grid

The integration of renewable energy generation into the electric grid is difficult, because of the source intermittency and inconsistency with energy usage. This situation can be improved through a system with energy-storage devices and distributed generators that not only mitigates fluctuations in generation and supply, but also reduces cost. In this paper we present application of energy source control and distributed generator planning in a small micro-grid system to improve energy usage efficiency and cost reduction. The optimized planning strategy is obtained using optimum energy storage and generation scheduling. Three scheduling methods, using real-time actual electricity usage and price, one-day-ahead prediction values and Model Predictive Control (MPC) methods are tested and their performances are compared. Results show that significant cost saving could be achieved with proper planning and coordination of various energy supply sources.

Modeling and revenue estimation of EV as reactive power service provider

Moving toward smart grid makes the distribution systems more active. In this dynamic environment, introducing new components such as Electric Vehicle (EV) can provide opportunities for Distribution System Operator (DSO) to improve the efficiency, economics, and sustainability of the production and distribution of electricity. For example, since reactive power support from EVs has short response time and does not affect the battery, reactive power support is a promising ancillary service that can be provided by EVs. This ancillary service is gaining more importance at distribution level where due to increased number of loads and the network topology, tracking the frequent changes in loads requires real time actions from local providers close to the loads. In this paper, we present a new model of EV operating as a reactive power service provider. We have included power ripple in the charger as a constraint in the proposed model. Our simulation results show the revue potential of providing reactive power service by EVs. This revenue amount is higher during peak hours because of increased demand from the DSO.

Modeling the gate more accurately for power MOSFETs

In recent years, power MOSFET devices have replaced the bipolar transistor. However, the power MOSFET is a fairly new device and current modeling techniques have not produced an accurate simulation of the gate to source. The method presented here generates a more accurate model of the transient behavior and gate to source characteristics of the power MOSFET. The results provide a better correlation between the MOSFET model and the actual device. >

Cadmium Telluride Thin Films on Silicon Substrates

Abstract : This report discusses the epitaxial growth of CdTe films on silicon substrates by the use of a closed hot wall epitaxy (CHWE) system. Deposition parameters were varied in order to determine the growth condition for obtaining good quality CdTe films. The characteristics of the films were investigated by scanning electron microscopy, x-ray diffraction and Auger electron spectroscopy. Experimental data show that no film grows when the source temperature is below 450 C. The film growth changes linearly with source temperature at a rate of 0. 0252 Angstrom/sec/dec C, and the best film was grown at a source temperature of 475 C. It was found that the lattice constant of the CdTe films was 6.487 + or - 0.004A.

Thin‐film thermocouple gauge

The importance of the thermocouple gauge in vacuum technology is well established. In this paper we present the fabrication and the calibration of a miniature thermocouple gauge using Cu–Cr thin films. The thermocouple gauge consists of a thin‐film Cr heater and a thin‐film Cu–Cr differential thermocouple on a glass substrate. The thin‐film Cu–Cr thermocouple was calibrated using a standard K‐type thermocouple. At constant temperature the change in the input power is a monotonic function of the change in the pressure. The measurement was repeated for several gases at a constant heater temperature of 100 °C. Experimental results show that our device can be used for a wide range of measurements. Owing to its small size, fabrication simplicity, and compatability with the existing thin‐film processing it is rather easy to incorporate our device with other integrated circuits.

Galvanic deposition of nanocrystalline ZnO thin films from a ZnO–Zn(OH)2 mixed phase precursor on p-Si substrate

A galvanic technique for the deposition of ZnO thin films is reported. The depositions were carried out on p-type single-crystal silicon substrates at room temperature, from a solution of ZnSO(4), where the Zn rod acted as a sacrificing anode and p-Si was the cathode. The deposition of ZnO by this method is pH sensitive, and a pH between 4 and 5 is found to be optimum for film deposition. This deposition technique is simple, inexpensive and can be carried out at room temperature. X-ray diffraction (XRD), scanning electron microscopy (SEM) and atomic force microscopy (AFM) studies revealed the nanocrystalline structure of the films. The resistivity of the annealed ZnO films was determined by the Van der Pauw measurement technique.

Comparison of silicon-on-insulator and Body-on-Insulator FinFET based digital circuits with consideration on self-heating effects

In recent years FinFET emerges as a promising device to assure the desired performance in the sub-22 nm regime. Among various FinFETs, SOI FinFET shows suppressed leakage current and superior short channel effects. However, it suffers from increased self-heating effect (SHE) due to the adaptation of a low thermal conductivity buried silicon dioxide layer and a ultra thin fin body. Bulk FinFET, on the other hand, mitigates the heating issue at the cost of the leakage current. Body-on-Insulator (BOI) FinFET alleviates, to some extent, the aforementioned downsides of both SOI and bulk FinFET but with the increased fabrication complexity [1]. Here, we report extensive simulation of BOI and SOI FinFETs using technology computer aided design (TCAD) [2] and for the first time, present evaluation of BOI and SOI FinFET based digital circuits and demonstrate that in actuality SHE is comparable for both circuits under low voltage bias.

A methodology to design a stochastic cost efficient DER scheduling considering environmental impact

Electric power generation and transportation sectors are considered as main sources of gas emission today. Renewable energy and Electric Vehicles (EV) show potential as promising solutions for emission reduction and energy cost saving. However, the integration of renewable energy generation into the electric grid can be difficult, because of the source intermittency and inconsistency with energy usage; uncontrolled EV charging can also impose more burdens on power systems. Those situations can be improved through coordinated charging of EVs and optimized operation of distributed generators (DG) that not only mitigates fluctuations in generation and supply, but also reduces energy cost and the emission of pollutants (CO2, SO2, and NOx). Emerging smart grid also brings new options for Distribution System Operator (DSO) toward efficient and sustainable operation of the network. One of these options is the use of Distributed Energy Resources (DER) including DG, EV, and Demand Response (DR). Operating DER has several advantages for DSO such as having DER close to load centers which reduces total network power loss. Since DSO has several energy sources to satisfy the electric load demand in the network, it is necessary to deploy optimal scheduling for efficient usage of available energy resources. In this paper we discuss a stochastic scheduling in the distribution network considering uncertainty in renewable energy generation. The proposed model can be used to analyse the effect of using DGs and EVs on emission and operation costs of the network. Results clearly shows that cost saving could be achieved with proper planning and coordination of various DERs.