Katie Coughlin

Analysis of Wind Power and Load Data at Multiple Time Scales

In this study we develop and apply new methods of data analysis for high resolution wind power and system load time series, to improve our understanding of how to characterize highly variable wind power output and the correlations between wind power and load. These methods are applied to wind and load data from the ERCOT region, and wind power output from the PJM and NYISO areas. We use a wavelet transform to apply mathematically well-defined operations of smoothing and differencing to the time series data. This approach produces a set of time series of the changes in wind power and load (or ?deltas?), over a range of times scales from a few seconds to approximately one hour. A number of statistical measures of these time series are calculated. We present sample distributions, and devise a method for fitting the empirical distribution shape in the tails. We also evaluate the degree of serial correlation, and linear correlation between wind and load. Our examination of the data shows clearly that the deltas do not follow a Gaussian shape; the distribution is exponential near the center and appears to follow a power law for larger fluctuations. Gaussian distributions are frequently used in modeling studies. These are likely to over-estimate the probability of small to moderate deviations. This in turn may lead to an over-estimation of the additional reserve requirement (hence the cost) for high penetration of wind. The Gaussian assumption provides no meaningful information about the real likelihood of large fluctuations. The possibility of a power law distribution is interesting because it suggests that the distribution shape for of wind power fluctuations may become independent of system size for large enough systems.

The Tariff Analysis Project: A database and analysis platform forelectricity tariffs

Much of the work done in energy research involves an analysis of the costs and benefits of energy-saving technologies and other measures from the perspective of the consumer. The economic value in particular depends on the price of energy (electricity, gas or other fuel), which varies significantly both for different types of consumers, and for different regions of the country. Ideally, to provide accurate information about the economic value of energy savings, prices should be computed directly from real tariffs as defined by utility companies. A large number of utility tariffs are now available freely over the web, but the complexity and diversity of tariff structures presents a considerable barrier to using them in practice. The goal of the Tariff Analysis Project (TAP) is to collect andarchive a statistically complete sample of real utility tariffs, and build a set of database and web tools that make this information relatively easy to use in cost-benefit analysis. This report presentsa detailed picture of the current TAP database structure and web interface. While TAP has been designed to handle tariffs for any kind of utility service, the focus here is on electric utilities withinthe United States. Electricity tariffs can be very complicated, so the database structures that have been built to accommodate them are quite flexible and can be easily generalized to other commodities.

Life-cycle cost and payback period analysis for commercial unitary air conditioners

LBNL-54244 Life-cycle Cost and Payback Period Analysis for Commercial Unitary Air Conditioners Greg Rosenquist, Katie Coughlin, Larry Dale, James McMahon, Steve Meyers Energy Analysis Department Environmental Energy Technologies Division Ernest Orlando Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 March 2004 This work was supported by the Office of Building Technologies of the U.S. Department of Energy, under Contract No. DE-AC03-76SF00098.

Physical Impacts of Climate Change on the Western US Electricity System: A Scoping Study

This paper presents an exploratory study of the possible physical impacts of climate change on the electric power system, and how these impacts could be incorporated into resource planning in the Western United States. While many aspects of climate change and energy have been discussed in the literature, there has not yet been a systematic review of the relationship between specific physical effects and the quantitative analyses that are commonly used in planning studies. The core of the problem is to understand how the electric system is vulnerable to physical weather risk, and how to make use of information from climate models to characterize the way these risks may evolve over time, including a treatment of uncertainty. In this paper, to provide the necessary technical background in climate science, we present an overview of the basic physics of climate and explain some of the methodologies used in climate modeling studies, particularly the importance of emissions scenarios. We also provide a brief survey of recent climate-related studies relevant to electric system planning in the Western US. To define the institutional context, we discuss the core elements of the resource and reliability planning processes used currently by utilities and by the Western Electricity Coordinating Council. To illustrate more precisely how climate-related risk could be incorporated into modeling exercises, we discuss three idealized examples. Overall, we argue that existing methods of analysis can and should be extended to encompass the uncertainties related to future climate. While the focus here is on risk related to physical impacts, the same principles apply to a consideration of how future climate change policy decisions might impact the design and functioning of the electric grid. We conclude with some suggestions and recommendations on how to begin developing this approach within the existing electric system planning framework for the West.

Valuing the Environmental Benefits of Urban WaterConservation

This report documents a project undertaken for the California Urban Water Conservation Council (the Council) to create a new method of accounting for the diverse environmental benefits of raw water savings. The environmental benefits (EB) model was designed to provide water utilities with a practical tool that they can use to assign a monetary value to the benefits that may accrue from implementing any of the Council-recommended Best Management Practices. The model treats only environmental services associated directly with water, and is intended to cover miscellaneous impacts that are not currently accounted for in any other cost-benefit analysis.

Tariff-based analysis of commercial building electricityprices

This paper presents the results of a survey and analysis ofelectricity tariffs and marginal electricity prices for commercialbuildings. The tariff data come from a survey of 90 utilities and 250tariffs for non-residential customers collected in 2004 as part of theTariff Analysis Project at LBNL. The goals of this analysis are toprovide useful summary data on the marginal electricity prices commercialcustomers actually see, and insight into the factors that are mostimportant in determining prices under different circumstances. We providea new, empirically-based definition of several marginal prices: theeffective marginal price and energy-only anddemand-only prices, andderive a simple formula that expresses the dependence of the effectivemarginal price on the marginal load factor. The latter is a variable thatcan be used to characterize the load impacts of a particular end-use orefficiency measure. We calculate all these prices for eleven regionswithin the continental U.S.

Documentation of Calculation Methodology, Input data, and Infrastructure for the Home Energy Saver Web Site

The Home Energy Saver (HES, http://HomeEnergySaver.lbl.gov) is an interactive web site designed to help residential consumers make decisions about energy use in their homes. This report describes the underlying methods and data for estimating energy consumption. Using engineering models, the site estimates energy consumption for six major categories (end uses); heating, cooling, water heating, major appliances, lighting, and miscellaneous equipment. The approach taken by the Home Energy Saver is to provide users with initial results based on a minimum of user input, allowing progressively greater control in specifying the characteristics of the house and energy consuming appliances. Outputs include energy consumption (by fuel and end use), energy-related emissions (carbon dioxide), energy bills (total and by fuel and end use), and energy saving recommendations. Real-world electricity tariffs are used for many locations, making the bill estimates even more accurate. Where information about the house is not available from the user, default values are used based on end-use surveys and engineering studies. An extensive body of qualitative decision-support information augments the analytical results.

Residential Electricity Prices: A Review of Data Sources and Estimation Methods

This paper presents an empirical study of residential electricity prices based on a compilation of tariff data collected for Lawrence Berkeley Lab’s Tariff Analysis Project (TAP). We also review other data sources commonly used to estimate residential sector electricity prices, including utility data published by the Energy Information Administration (EIA), the Typical Bills reports published by the Edison Electric Institute, and household-level electricity consumption and expenditure data included with the EIA’s Residential Energy Consumption Surveys. We define three different types of price that can be estimated from the data, construct estimation methods, compare the results and evaluate the relative strengths and weaknesses of each approach. We examine several sources of variation including seasonal, regional, industry structure, and the magnitude of baseline household consumption. The tariff data are also used to explore the impact of moving households from standard tariffs to time-of-use pricing, and to summarize how this affects predictions of electricity bill savings for both demand reduction and demand shifting. ∗This work was supported by the Office of Energy Efficiency and Renewable Energy, Building Technologies Program, of the U.S. Department of Energy under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH11231.

Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results.

Modeling the Capacity and Emissions Impacts of Reduced Electricity Demand. Part 1. Methodology and Preliminary Results. Katie Coughlin, Hongxia Shen, Peter Chan, Brian McDevitt, and Andrew Sturges Energy Analysis Department Environmental Energy Technologies Division Lawrence Berkeley National Laboratory Berkeley, CA 94720 February 2013 This work was supported by the Director, Office of Science, Office of Basic Energy Sciences, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Modeling National Impacts for the Building America Program

In this paper we present a model to estimate the nationalenergy and economic impacts of the Department of Energy Building Americaprogram. The program goal is to improve energy performance in newresidential construction, by working with builders to design andconstruct energy-efficient homes at minimal cost. The model is anadaptation of the method used to calculate the national energy savingsfor appliance energy efficiency standards. The main difference is thatthe key decision here is not the consumer decision to buy anefficienthouse, but rather the builder decision to offer such a house inthe market. The builder decision is treated by developing a number ofscenarios in which the relative importance of first costs vs. energysavings is varied.