Andrew Mills

Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

This report--the first in what is envisioned to be an ongoing annual series--attempts to fill this need by providing a detailed overview of developments and trends in the U.S. wind power market, with a particular focus on 2006.

Implications of Wide-Area Geographic Diversity for Short- Term Variability of Solar Power

LBNL-3884E E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY Implications of Wide-Area Geographic Diversity for Short- Term Variability of Solar Power Andrew Mills and Ryan Wiser Environmental Energy Technologies Division September 2010 Download from http://eetd.lbl.gov/EA/EMP The work described in this paper was funded by the U.S. Department of Energy (Office of Energy Efficiency and Renewable Energy and Office of Electricity Delivery and Energy Reliability) under Contract No. DE-AC02-05CH11231.

The Cost of Transmission for Wind Energy: A Review of Transmission Planning Studies

LBNL- E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY The Cost of Transmission for Wind Energy: A Review of Transmission Planning Studies Andrew Mills, Ryan Wiser, and Kevin Porter Environmental Energy Technologies Division February 2009 Download from http://eetd.lbl.gov/EA/EMP The work described in this report was funded by the Office of Energy Efficiency and Renewable Energy (Wind & Hydropower Technologies Program) and by the Office of Electricity Delivery and Energy Reliability (Permitting, Siting and Analysis Division) of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Dark Shadows: Understanding Variability and Uncertainty of Photovoltaics for Integration with the Electric Power System

The U.S. Department of Energys National Renewable Energy Laboratory, Sandia National Laboratories, the Solar Electric Power Association, the Utility Wind Integration Group, and the U.S. Department of Energy hosted a day-long public workshop on the variability of photovoltaic (PV) plants. The workshop brought together utilities, PV system developers, power system operators, and several experts to discuss the potential impacts of PV variability and uncertainty on power system operations.

Mass Market Demand Response and Variable Generation Integration Issues: A Scoping Study

This scoping study focuses on the policy issues inherent in the claims made by some Smart Grid proponents that the demand response potential of mass market customers which is enabled by widespread implementation of Advanced Metering Infrastructure (AMI) through the Smart Grid could be the “silver bullet” for mitigating variable generation integration issues. In terms of approach, we will: identify key issues associated with integrating large amounts of variable generation into the bulk power system; identify demand response opportunities made more readily available to mass market customers through widespread deployment of AMI systems and how they can affect the bulk power system; assess the extent to which these mass market Demand Response (DR) opportunities can mitigate Variable Generation (VG) integration issues in the near-term and what electricity market structures and regulatory practices could be changed to further expand the ability for DR to mitigate VG integration issues over the long term; and provide a qualitative comparison of DR and other approaches to mitigate VG integration issues.

Implications of geographic diversity for short-term variability and predictability of solar power

Worldwide interest in the deployment of photovoltaic generation (PV) is rapidly increasing. Operating experience with large PV plants, however, demonstrates that large, rapid changes in the output of PV plants are possible. Early studies of PV grid impacts suggested that short-term variability could be a potential limiting factor in deploying PV. Many of these early studies, however, lacked high-quality data from multiple sites to assess the costs and impacts of increasing PV penetration. As is well known for wind, accounting for the potential for geographic diversity can significantly reduce the magnitude of extreme changes in aggregated PV output, the resources required to accommodate that variability, and the potential costs of managing variability. We use measured 1-min solar insolation for 23 time-synchronized sites in the Southern Great Plains network of the Atmospheric Radiation Measurement program and wind speed data from 10 sites in the same network to characterize the variability of PV with different degrees of geographic diversity and to compare the variability of PV to the variability of similarly sited wind. We find in our analysis of PV and wind plants similarly sited in a 5 × 5 grid with 50 km spacing that the variability of PV is only slightly more than the variability of wind on time scales of 5–15 min. Over shorter and longer time scales the level of variability is nearly identical. Finally, we use a simple approximation method to estimate the cost of carrying additional reserves to manage sub-hourly variability. We conclude that the costs of managing the short-term variability of PV are dramatically reduced by geographic diversity and are not substantially different from the costs for managing the short-term variability of similarly sited wind in this region.

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

There exist several different reliability- and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.

Financial impacts of net-metered PV on utilities and ratepayers: A scoping study of two prototypical U.S. utilities

Author(s): Satchwell, Andrew; Mills, Andrew; Barbose, Galen; Wiser, Ryan; Cappers, Peter; Darghouth, Naim

Capacity value of solar power

Evaluating the capacity value of renewable energy sources can pose significant challenges due to their variable and uncertain nature. In this paper the capacity value of solar power is investigated. Solar capacity value metrics and their associated calculation methodologies are reviewed and several solar capacity studies are summarized. The differences between wind and solar power are examined, the economic importance of solar capacity value is discussed and other assessments and recommendations are presented.

Integrating Solar PV in Utility System Operations

LBNL-XXXX E RNEST O RLANDO L AWRENCE B ERKELEY N ATIONAL L ABORATORY Integrating Solar PV in Utility System Operations A. Mills 1 , A. Botterud 2 , J. Wu 2,4 , Z. Zhou 2 , B-M. Hodge 3 , M. Heany 3 Environmental Energy Technologies Division October 2013 Lawrence Berkeley National Laboratory Argonne National Laboratory National Renewable Energy Laboratory University of Chicago Lawrence Berkeley National Laboratory’s contribution to this work was funded by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (Solar Energy Technologies Office) under Lawrence Berkeley National Laboratory Contract No. DE-AC02-05CH112