Browsing by Subject "Energy efficiency"

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Design and control of integrated systems for hydrogen production and power generation
(2013-11) Georgis, Dimitrios
Growing concerns on CO₂ emissions have led to the development of highly efficient power plants. Options for increased energy efficiencies include alternative energy conversion pathways, energy integration and process intensification. Solid oxide fuel cells (SOFC) constitute a promising alternative for power generation since they convert the chemical energy electrochemically directly to electricity. Their high operating temperature shows potential for energy integration with energy intensive units (e.g. steam reforming reactors). Although energy integration is an essential tool for increased efficiencies, it leads to highly complex process schemes with rich dynamic behavior, which are challenging to control. Furthermore, the use of process intensification for increased energy efficiency imposes an additional control challenge. This dissertation identifies and proposes solutions on design, operational and control challenges of integrated systems for hydrogen production and power generation. Initially, a study on energy integrated SOFC systems is presented. Design alternatives are identified, control strategies are proposed for each alternative and their validity is evaluated under different operational scenarios. The operational range of the proposed control strategies is also analyzed. Next, thermal management of water gas shift membrane reactors, which are a typical application of process intensification, is considered. Design and operational objectives are identified and a control strategy is proposed employing advanced control algorithms. The performance of the proposed control strategy is evaluated and compared with classical control strategies. Finally SOFC systems for combined heat and power applications are considered. Multiple recycle loops are placed to increase design flexibility. Different operational objectives are identified and a nonlinear optimization problem is formulated. Optimal designs are obtained and their features are discussed and compared. The results of the dissertation provide a deeper understanding on the design, operational and control challenges of the above systems and can potentially guide further commercialization efforts. In addition to this, the results can be generalized and used for applications from the transportation and residential sector to large--scale power plants.
Distributed optimization in an energy-constrained network.
(2010-02) Razavi Majomard, Seid Alireza
We consider a distributed optimization problem whereby a network of N nodes, Sℓ, ℓ ∈ {1, . . . ,N}, wish to minimize a common strongly convex function f(x), x = [x1, . . . , xN]T , under the constraint that node Sℓ controls variable xℓ only. The nodes locally update their respective variables and periodically exchange their values over a set of pre-defined communication channels. Previous studies of this problem have focused mainly on the convergence issue and the analysis of convergence rate. In this work, we consider noisy communication channels and study the impact of communication energy on convergence. In particular, we study the minimum amount of communication energy required for nodes to obtain an ϵ-minimizer of f(x) in the mean square sense. For linear analog communication schemes, we prove that the communication energy to obtain an ϵ-minimizer of f(x) must grow at least at the rate of Ω(1/ϵ), and this bound is tight when f is convex quadratic. Furthermore, we show that the same energy requirement can be reduced to O ( log2 1/ϵ ) if suitably designed digital communication schemes are used.
EnergyPlus Energy Simulation Software
(2014) Gerber, Michael
Modeling and design space exploration of storage processing unit for energy efficiency
(2015-02) Nagarajan, Ashwin
Computer architectures in the present era of exascale computing and big data face two major challenges - (i) Increasing gap between processor and memory/storage speeds and (ii) Energy Consumption. A compute system that tightly couples data storage and computation is an attractive solution to mitigate these challenges. By implementing processing inside NAND Flash SSDs computation is moved closer to data. In fact, a computational hierarchy, named Storage Processing Unit (SPU), is formed with processing elements in NAND Flash Memory Controller, SSD controller and host general purpose processor. This hierarchy offers unique opportunities to curtail data movement and reduce energy consumption. This thesis models SPU architecture, explores the design space using carefully chosen applications and associated optimizations to understand and evaluate its energy and performance. Sparse BLAS, BFS, K-Means Clustering and K-Nearest Neighbor are used as benchmarks with energy and performance gains observed up to 11x-400x and 4x-66x respectively.
Momentum - Fall 2010
(2010) University of Minnesota: Institute on the Environment
Renewable energy deployment in the electricity sector: three essays on policy design, scope, and outcomes
(2010-11) Fischlein, Miriam Lydia
Due to the large environmental impact of the electric energy sector, evaluating the policy instruments employed in this arena is a particularly pressing issue. In the United States, state policy is a major driver of sustainable energy development and provides a unique opportunity to conduct comparative policy research. Thirty-two states have implemented a renewable portfolio standard (RPS), a policy instrument that mandates renewable resource use. Although similar on the surface, these policies present staggering variation in the design elements they incorporate. This dissertation investigates patterns of policy design, scope and outcomes of RPS, contributing to the literature on policy design and effectiveness, and expanding the empirical knowledge of state sustainable energy policies. The first essay presents an in-depth state-by-state analysis of RPS design elements, complemented by the development of a policy classification scheme. Examining RPS design under the angle of stringency of goals, discretion in means, and strength of the enforcement regime introduces a measure of comparability. It highlights that a rigid focus on singular measures of policy strength and broad policy types detracts from understanding the impact of individual design features. The second essay underlines this argument, relating RPS design characteristics quantitatively to policy response. The results show that both more stringent goals and, to some extent, increased discretion in means are associated with higher policy response. The research design used is innovative, in that it accounts for the full complexity of RPS, while measuring outcomes at the level the policy targets (retail sales). The final essay concentrates on a single design attribute, policy scope. Focusing on a sector currently excluded from most state sustainable energy policies - consumer-owned utilities - it assesses future policy scenarios for their inclusion. To remediate the complete lack of emissions data on consumer-owned utilities, it develops for the first time a method to estimate the carbon intensity of electricity sales from this sector. Based on these estimates, future carbon management scenarios are developed for the inclusion of consumer-owned utilities in renewable policies, including interaction with energy efficiency policies.
State of Sustainability Practices among Minnesota Tourism Businesses, 2007-2013
(2013-10-29) Qian, Xinyi; Schneider, Ingrid E.; qianx@umn.edu; Qian, Xinyi
The dataset was used in three major ways. First, using data collected in 2013, we documented the current attitude towards sustainability practices among tourism businesses in Minnesota, particularly how they perceive the benefits and difficulties of implementing these practices. We also documented the extent of implementation of six types of sustainability practices, including energy efficiency, waste minimization, environmental purchasing, air quality, water conservation, and landscaping/wildlife. Second, we assessed whether attitude towards sustainability practices and the extent of implementing various practices changed over time (i.e., across the three surveys). Lastly, we benchmarked current level of knowledge of invasive species among Minnesota tourism businesses using data from the 2013 survey. This is the first time that the survey includes questions that assess knowledge of invasive species, providing a benchmarking opportunity. We want to release this dataset, because there is little research that documents the extent to which different types of sustainability practices are implemented among tourism businesses in the state of Minnesota. The tourism industry makes significant contributions to the state's economy, at the same time, relying on the many natural assets that the state has to continue attracting visitors. Therefore, it is important that the tourism industry contributes to, rather than deters, the progress of sustainability practices. We believe that releasing this dataset will help increase public awareness of and interest in the trend of implementing sustainability practices among tourism businesses in Minnesota.
A statistical approach to error prediction in approximate sequential circuits
(2014-09) Kapare, Amrut Shivshankar
Low power and high performance requirements have increased focus on. Approximate Computing which uses designs that approximate the functionality of a precise design while still achieving acceptable quality of results and consuming lower nergy than the precise designs. To perform design automation for approximate designs, modern CAD tools should have the ability to quickly estimate the output quality of designs that include approximate design modules. Previous research on output quality estimation for approximate designs has focused on using an interval based approach which introduces quantization error, or lookup table-based techniques, which mainly emphasize on output quality estimation for approximate combinational circuits and have large overheads for storing the lookup tables for different error metrics. Other works use an unrolling based approach to estimate the output quality which requires large characterization time. In this work, I propose a methodology to estimate the output quality of approximate sequential circuits based on deriving analytical expressions for predicting approximation errors from statistical data gathered from performing limited characterization of the approximate circuits. I show that limited characterization is sufficient to accurately characterize approximation errors since in many cases, the error behavior of approximate circuits follows a pattern. As such, I show that we can achieve high accuracy of prediction for average approximation error, even with this limited characterization. I also demonstrate that the methodology is more scalable and reduces characterization time by 90% on average compared to previous approaches.

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