Thermoelectric properties of Pb0.75-xMnxSn0.25Te alloys with variable manganese content

Lead tin telluride is one of the well-established thermoelectric materials in the temperature range 350-750 K. In the present study, Pb0.75-xMnxSn0.25Te1.00 alloys with variable manganese (Mn) content were prepared by solid state synthesis and the thermoelectric properties were studied. X-ray diffraction, (XRD) showed that the samples followed Vegard's law, indicating solid solution formation and substitution of Mn at the Pb site. Scanning Electron Microscopy (SEM) showed that the grain sizes varied from <1 mu m to more than 10 mu m and MnTe rich phase was present for higher Mn content. Seebeck coefficient, electrical resistivity and thermal conductivity were measured from room temperature to 720 K. At 300 K, large Seebeck values were obtained, possibly due to increased effective mass on Mn substitution and low carrier concentration of the samples. At higher temperatures, transition from n-type to p-type indicated the presence of thermally generated carriers. Temperature dependent electrical resistivity showed the transition from degenerate to non-degenerate behavior. For thermal conductivity, low values (similar to 1 W/m-K at 300 K) were obtained. At higher temperatures bipolar conduction was observed, in agreement with the Seebeck and resistivity data. Due to low power factor, the maximum thermoelectric figure of merit (zT) was limited to 0.23 at 329 K for the sample with lowest Mn content (x=0.03). (C) 2015 Elsevier Ltd. All rights reserved.

Thermoelectric properties of Co substituted synthetic tetrahedrite

Transition metal atom (Co) substituted synthetic tetrahedrite compounds Cu12-xCoxSb4S13 (x = 0, 0.5, 1.0, 1.5, 2.0) were prepared by solid state synthesis. X-Ray Diffraction (XRD) patterns revealed tetrahedrite as the main phase, whereas for the compounds with x = 0, 0.5 a trace of impurity phase Cu3SbS4 was observed. The surface morphology showed a large grain size with low porosity, which indicated appropriate compaction for the hot pressed samples. The phase purity, as monitored by Electron Probe Micro Analysis (EPMA) is in good agreement with the XRD data. The elemental composition for all the compounds almost matched with the nominal composition. The X-ray Photoelectron Spectroscopy (XPS) data showed that Cu existed in both +1 and +2 states, while Sb exhibited +3 oxidation states. Elastic modulus and hardness showed a systematic variation with increasing Co content. The electrical resistivity and Seebeck coefficient increased with increase in the doping content due to the decrease in the number of carriers caused by the substitution of Co2+ on the Cu1+ site. The positive Seebeck coefficient for all samples indicates that the dominant carriers are holes. A combined effect of resistivity and Seebeck coefficient leads to the maximum power factor of 1.76 mW m(-1) K-2 at 673 K for Cu11.5Co0.5Sb4S13. This could be due to the optimization in the carrier concentration by the partial substitution of Co2+ on both the Cu1+ as well as Cu2+ site at the same doping levels, which is also supported by the XPS data. The total thermal conductivity systematically decreased with increase of doping content as it is mainly influenced by the decrease of carrier thermal conductivity. The maximum thermoelectric figure of merit zT = 0.98 was obtained at 673 K for Cu11.5Co0.5Sb4S13. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

High temperature thermoelectric properties of Zr and Hf based transition metal dichalcogenides: A first principles study

We investigate the electronic and thermal transport properties of bulk MX2 compounds (M = Zr, Hf and X = S, Se) by first-principles calculations and semi-classical Boltzmann transport theory. The band structure shows the confinement of heavy and light bands along the out of plane and in-plane directions, respectively. This results in high electrical conductivity (sigma) and large thermopower leading to a high power factor (S-2 sigma) for moderate n-type doping. The phonon dispersion demonstrates low frequency flat acoustical modes, which results in low group velocities (v(g)). Consequently, lowering the lattice thermal conductivity (kappa(latt)) below 2 W/m K. Low kappa(latt) combined with high power factor results in ZT > 0.8 for all the bulk MX2 compounds at high temperature of 1200 K. In particular, the ZT(max) of HfSe2 exceeds 1 at 1400 K. Our results show that Hf/Zr based dichalcogenides are very promising for high temperature thermoelectric application. (C) 2015 AIP Publishing LLC.

Thermoelectric Properties of In-Doped Cu2ZnGeSe4

Recently, much research has been focused on finding new thermoelectric materials. Cu-based quaternary chalcogenides that belong to A(2)BCD(4) (A = Cu; B = Zn, Cd; C = Sn, Ge; D = S, Se, Te) are wide band gap materials and one of the potential thermoelectric materials due to their complex crystal structures. In this study, In-doped quaternary compounds Cu2ZnGe1-xInxSe4 (x = 0, 0.025, 0.05, 0.075, 0.1) were prepared by a solid state synthesis method. Powder x-ray diffraction patterns of all the samples showed a tetragonal crystal structure (space group I-42m) of the main phase with a trace amount of impurity phases, which was further confirmed by Rietveld analysis. The elemental composition of all the samples showed a slight deviation from the nominal composition with the presence of secondary phases. All the transport properties were measured in the temperature range 373-673 K. The electrical resistivity of all the samples initially decreased up to similar to 470 K and then increased with increase in temperature upto 673 K, indicating the transition from semiconducting to metallic behavior. Positive Seebeck coefficients for all the samples revealed that holes are the majority carriers in the entire temperature range. The substitution of In3+ on Ge4+ introduces holes and results in the decrease of resistivity as well as the Seebeck coefficient, thereby leading to the optimization of the power factor. The lattice thermal conductivity of all the samples decreased with increasing temperature, indicating the presence of phonon-phonon scattering. As a result, the thermoelectric figure of merit (zT) of the doped sample showed an increase as compared to the undoped compound.

Optimization and Control of Power Flow in Distribution Networks

Climate change is arguably the most critical issue facing our generation and the next. As we move towards a sustainable future, the grid is rapidly evolving with the integration of more and more renewable energy resources and the emergence of electric vehicles. In particular, large scale adoption of residential and commercial solar photovoltaics (PV) plants is completely changing the traditional slowly-varying unidirectional power flow nature of distribution systems. High share of intermittent renewables pose several technical challenges, including voltage and frequency control. But along with these challenges, renewable generators also bring with them millions of new DC-AC inverter controllers each year. These fast power electronic devices can provide an unprecedented opportunity to increase energy efficiency and improve power quality, if combined with well-designed inverter control algorithms. The main goal of this dissertation is to develop scalable power flow optimization and control methods that achieve system-wide efficiency, reliability, and robustness for power distribution networks of future with high penetration of distributed inverter-based renewable generators.

Proposed solutions to power flow control problems in the literature range from fully centralized to fully local ones. In this thesis, we will focus on the two ends of this spectrum. In the first half of this thesis (chapters 2 and 3), we seek optimal solutions to voltage control problems provided a centralized architecture with complete information. These solutions are particularly important for better understanding the overall system behavior and can serve as a benchmark to compare the performance of other control methods against. To this end, we first propose a branch flow model (BFM) for the analysis and optimization of radial and meshed networks. This model leads to a new approach to solve optimal power flow (OPF) problems using a two step relaxation procedure, which has proven to be both reliable and computationally efficient in dealing with the non-convexity of power flow equations in radial and weakly-meshed distribution networks. We will then apply the results to fast time- scale inverter var control problem and evaluate the performance on real-world circuits in Southern California Edison’s service territory.

The second half (chapters 4 and 5), however, is dedicated to study local control approaches, as they are the only options available for immediate implementation on today’s distribution networks that lack sufficient monitoring and communication infrastructure. In particular, we will follow a reverse and forward engineering approach to study the recently proposed piecewise linear volt/var control curves. It is the aim of this dissertation to tackle some key problems in these two areas and contribute by providing rigorous theoretical basis for future work.

Survey on the idle capacity of fish processing (freezing) plants in India - 1. West Coast

The extent of idle capacity in fish processing (freezing) plants estimated by stratified random sampling is reported. The estimates for 1978 and 1979 for the processing plants on the west coast of India were 76.9 % and 73.2 % respectively at the rate of 250 working days per annum and two shifts per day. The percentage error of estimates worked out to 6.04 for 1978 and 6.98 for 1979. Substantial under utilization of processing plants noticed in all the states accounts mainly to the non-availability of raw material (prawn), high cost of production and shortage of power.

Survey on the idle capacity of fish processing (freezing) plants in India - 2. East coast

The extent of idle capacity in the fish processing (freezing) plants in the east coast of India estimated by stratified random sampling and the factors responsible for the same are reported. The estimates of idle capacity of fish processing plants in the east coast for the years 1978 and 1979 were respectively 75.9% and 72.5% on the basis of 250 working days per annum and double shift per day. The percentage errors of estimates worked out to 6.9 for 1978 and 4.7 for 1979. The corresponding figures were worked out on the basis of 200 working days also. Substantial under-utilisation of plants in all the maritime states in the east coast accounted mainly to non-availability of raw material, high cost of production, shortage of power, scarcity of ice and potable water during peak season and frequent labour troubles.

Operational characteristics of a 1.2-MW biomass gasification and power generation plant

In this study, we analyzed the operational characteristics of a 1.2-MW rice husk gasification and power generation plant located in Changxing, Zhejiang province, China. The influences of gasification temperature, equivalence ratio (ER), feeding rate and rice husk water content on the gasification characteristics in a fluidized bed gasifier were investigated. The axial temperature profile in the dense phase of the gasifier showed that inadequate fluidization occurred inside the bed, and that the temperature was closely related to changes in ER and feeding rate. The bed temperature increased linearly with increasing ER when the feeding rate was kept constant, while a higher feeding rate corresponded to a lower bed temperature at fixed ER. The gas heating value decreased with increasing temperature, while the feeding rate had little effect. When the gasification temperature was 700-800C, the gas heating value ranged from 5450-6400kJ/Nm3. The water content of the rice husk had an obvious influence on the operation of the gasifier: increases in water content up to 15% resulted in increasing ER and gas yield, while water contents above 15% caused aberrant temperature fluctuations. The problems in this plant are discussed in the light of operational experience of MW-scale biomass gasification and power generation plants.

Combined heat and power and campus carbon footprint reduction

Gemstone Team Cogeneration Technology

Computational scheduling methods for integrating plug-in electric vehicles with power systems: a review

Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

Efficiency assessment of electricity power generation on Ireland’s Single Electricity Market by Data Envelopment Analysis

The efficiency of generation plants is an important measure for evaluating the operating performance. The objective of this paper is to evaluate electricity power generation by conducting an All-Island-Generator-Efficiency-Study (AIGES) for the Republic of Ireland and Northern Ireland by utilising a Data Envelopment Analysis (DEA) approach. An operational performance efficiency index is defined and pursued for the year 2008. The economic activities of electricity generation units/plants examined in this paper are characterized by numerous input and output indicators. Constant returns to scale (CRS) and variable returns to scale (VRS) type DEA models are employed in the analysis. Also a slacks based analysis indicates the level of inefficiency for each variable examined. The findings from this study provide a general ranking and evaluation but also facilitate various interesting efficiency comparisons between generators by fuel type.

Real-time estimation of battery internal temperature based on a simplified thermoelectric model

Li-ion batteries have been widely used in the EVs, and the battery thermal management is a key but challenging part of the battery management system. For EV batteries, only the battery surface temperature can be measured in real-time. However, it is the battery internal temperature that directly affects the battery performance, and large temperature difference may exist between surface and internal temperatures, especially in high power demand applications. In this paper, an online battery internal temperature estimation method is proposed based on a novel simplified thermoelectric model. The battery thermal behaviour is first described by a simplified thermal model, and battery electrical behaviour by an electric model. Then, these two models are interrelated to capture the interactions between battery thermal and electrical behaviours, thus offer a comprehensive description of the battery behaviour that is useful for battery management. Finally, based on the developed model, the battery internal temperature is estimated using an extended Kalman filter. The experimental results confirm the efficacy of the proposed method, and it can be used for online internal temperature estimation which is a key indicator for better real-time battery thermal management.

Radio Frequency Synthesis for Power-Constrained Systems

Thesis (Ph.D.)--University of Washington, 2015

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.