C. Lindsay Anderson

Bio: C. Lindsay Anderson is an academic researcher from Cornell University. The author has contributed to research in topics: Wind power & Electric power system. The author has an hindex of 10, co-authored 44 publications receiving 694 citations. Previous affiliations of C. Lindsay Anderson include University of Western Ontario.

A New Wavelet Denoising Method for Selecting Decomposition Levels and Noise Thresholds

Abstract: A new method is presented to denoise 1-D experimental signals using wavelet transforms. Although the state-of-the-art wavelet denoising methods perform better than other denoising methods, they are not very effective for experimental signals. Unlike images and other signals, experimental signals in chemical and biophysical applications, for example, are less tolerant to signal distortion and under-denoising caused by the standard wavelet denoising methods. The new method: 1) provides a method to select the number of decomposition levels to denoise; 2) uses a new formula to calculate noise thresholds that does not require noise estimation; 3) uses separate noise thresholds for positive and negative wavelet coefficients; 4) applies denoising to the approximation component; and 5) allows the flexibility to adjust the noise thresholds. The new method is applied to continuous wave electron spin resonance spectra and it is found that it increases the signal-to-noise ratio (SNR) by more than 32 dB without distorting the signal, whereas standard denoising methods improve the SNR by less than 10 dB and with some distortion. In addition, its computation time is more than six times faster.

Secure Planning and Operations of Systems With Stochastic Sources, Energy Storage, and Active Demand

Abstract: This work presents a stochastic optimization framework for operations and planning of an electricity network as managed by an Independent System Operator. The objective is to maximize the total expected net benefits over the planning horizon, incorporating the costs and benefits of electricity consumption, generation, ancillary services, load-shedding, storage and load-shifting. The overall framework could be characterized as a secure, stochastic, combined unit commitment and AC optimal power flow problem, solving for an optimal state-dependent schedule over a pre-specified time horizon. Uncertainty is modeled to expose the scenarios that are critical for maintaining system security, while properly representing the stochastic cost. The optimal amount of locational reserves needed to cover a credible set of contingencies in each time period is determined, as well as load-following reserves required for ramping between time periods. The models for centrally-dispatched storage and time-flexible demands allow for optimal tradeoffs between arbitraging across time, mitigating uncertainty and covering contingencies. This paper details the proposed problem formulation and outlines potential approaches to solving it. An implementation based on a DC power flow model solves systems of modest size and can be used to demonstrate the value of the proposed stochastic framework.

Mobility of Multiwalled Carbon Nanotubes in Porous Media

Abstract: Engineered multiwalled carbon nanotubes (MWCNTs) are the subject of intense research and are expected to gain widespread usage in a broad variety of commercial products. However, concerns have been raised regarding potential environmental and human health risks. The mobility of MWCNTs in porous media is examined in this study using one-dimensional flow-through column experiments under conditions representative of subsurface and drinking water treatment systems. Results demonstrate that pore water velocity strongly influenced MWCNT transport, with high MWCNT mobility at pore water velocities greater than 4.0 m/d. A numerical simulator, which incorporated a newly developed theoretical collector efficiency relationship for MWCNTs in spherical porous media, was developed to model observed column results. The model, which incorporated traditional colloid filtration theory in conjunction with a site-blocking term, yielded good agreement with observed results in quartz sand-packed column experiments. Experiments were also conducted in glass bead-packed columns with the same mean grain size as the quartz sand-packed columns. MWCNTs were more mobile in the glass bead-packed columns.

A Flexible Dispatch Margin for Wind Integration

Abstract: Integrating wind power into power systems contributes to existing variability in system operations. Current methods to mitigate this variability and uncertainty focus on using conventional generator ramping capability. There is also the option of using wind power itself to mitigate the variability and uncertainty that it introduces into the system. This paper introduces the concept of a flexible dispatch margin as a means for wind to participate in mitigating net variability and net uncertainty. In providing a flexible dispatch margin, wind generators under-schedule in the hour-ahead energy market in order to have additional expected flexibility available for the real-time market. The implementation of the flexible dispatch margin is analyzed in a two-stage optimization model with recourse to the flexible dispatch margin, flexible demand and generator ramping. This modeling framework combines Monte Carlo simulations with AC OPF analysis, using the IEEE 39-bus test system. Results show that use of the flexible dispatch margin decreases the reliance on peaking generators to mitigate net variability and uncertainty, and also decreases the frequency of price spike events, particularly as wind penetration increases from 10% to 30%. The analysis emphasizes the importance of increasing flexible resource capability as power system variability and uncertainty increase.

When is nearest neighbor meaningful

Abstract: We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

Aggregation and deposition of engineered nanomaterials in aquatic environments: role of physicochemical interactions.

Abstract: The ever-increasing use of engineered nanomaterials will lead to heightened levels of these materials in the environment. The present review aims to provide a comprehensive overview of current knowledge regarding nanoparticle transport and aggregation in aquatic environments. Nanoparticle aggregation and deposition behavior will dictate particle transport potential and thus the environmental fate and potential ecotoxicological impacts of these materials. In this review, colloidal forces governing nanoparticle deposition and aggregation are outlined. Essential equations used to assess particle−particle and particle−surface interactions, along with Hamaker constants for specific nanoparticles and the attributes exclusive to nanoscale particle interactions, are described. Theoretical and experimental approaches for evaluating nanoparticle aggregation and deposition are presented, and the major findings of laboratory studies examining these processes are also summarized. Finally, we describe some of the chall...

Introduction to Spectroscopy

Abstract: Spectroscopy is the study of matter interacting with electromagnetic radiation (e.g., light). The electromagnetic spectrum in Figure 1 illustrates the many different types of electromagnetic radiation, including gamma rays (γ-rays), X-rays, ultraviolet (UV) radiation, visible light, infrared (IR) radiation, microwaves, and radio waves. The frequency (ν) and wavelength (λ) ranges associated with each form of radiant energy are also indicated in Figure 1.

Pumped hydro energy storage system: A technological review

Abstract: The pumped hydro energy storage (PHES) is a well-established and commercially-acceptable technology for utility-scale electricity storage and has been used since as early as the 1890s. Hydro power is not only a renewable and sustainable energy source, but its flexibility and storage capacity also make it possible to improve grid stability and to support the deployment of other intermittent renewable energy sources such as wind and solar. As a result, a renewed interest in PHES and a demand for the rehabilitation of old small hydro power plants are emerging globally. With regard to PHES, advances in turbine design are required to enhance plant performance and flexibility and new strategies for optimizing storage capacity and for maximizing plant profitability in the deregulated energy market. In the early 2000s, this technology has again emerged as an economically and technologically acceptable option for peak load shaving and wind and solar energy storage for power quality assurance. Furthermore, renewable energy sources due to their fluctuating nature cannot maintain or regulate continuous supply of power and hence require bulk electricity storage. The present study aims at reviewing the existing global PHES capacities, technological development, and hybrid systems (wind-hydro, solar pv-hydro, and wind-pv-hydro) and recommending the best possible options. The review explores that PHES is the most suitable technology for small autonomous island grids and massive energy storage, where the energy efficiency of PHES varies in practice between 70% and 80% with some claiming up to 87%. Around the world, PHES size mostly nestles in the range of 1000–1500 MW, being as large as 2000–3000 MW. On the other hand, photovoltaic based pumped storage systems have been used for very small scale (load of few houses) only.