DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Sarah Becker , Bethany A. Frew, Gorm B. Andresen,Timo Zeyer, Stefan Schramm, Martin Greiner, Mark Z. Jacobson
A future energy system is likely to rely heavily on wind and solar PV. To quantify general features of such a weather dependent electricity supply in the contiguous US, wind and solar PV generation data are calculated, based on 32 years of weather data with temporal resolution of 1 h and spatial resolution of 40 x 40 square km, assuming site-suitability-based and stochastic wind and solar capacity distributions. The regional wind-and-solar mixes matching load and generation closest on seasonal timescales cluster around 80% solar share, owing to the US summer load peak. This mix more than halves long-term storage requirements, compared to wind only. The mixes matching generation and load best on daily timescales lie at about 80% wind share, due to the nightly gap in solar production. Going from solar only to this mix reduces backup energy needs by about 50%. Furthermore, we calculate shifts in FERC (Federal Energy Regulatory Commission)-level LCOE (Levelized Costs Of Electricity) for wind and solar PV due to differing weather conditions. Regional LCOE vary by up to 29%, and LCOE-optimal mixes largely follow resource quality. A transmission network enhancement among FERC regions is constructed to transfer high penetrations of solar and wind across FERC boundaries, employing a novel least-cost optimization.
CO2 and air pollution emission reduction goals as well as energy security, price stability, and affordability considerations make renewable electricity generation attractive. A highly renewable electricity supply will be based to a large extent on wind and solar photovoltaic (PV) power, since these two resources are both abundant and either relatively inexpensive or rapidly becoming cost competitive. Such a system demands a fundamentally different design approach: While electricity generation was traditionally constructed to be dispatchable in order to follow the demand, wind and solar PV power output is largely determined by weather conditions that are out of human control. We therefore collectively term them VRES (variable renewable energy sources).
Spatial aggregation has a favorable impact on generation characteristics, as was found both for wind and solar PV power in numerous studies [2e9]. Especially for wind, smoothing effects are much more pronounced on large scales, as can be seen from the comparison of the US East coast (about 3000 500 km2), discussed in Ref. , to Denmark (about 200 300 km2), cf. Ref. . In spite of the leveling effects of aggregation, there is still a considerable mismatch between load and generation left, which is partly due also to load variability.
This paper aims to identify general design features for the US power system with a high share of wind and solar PV. While several studies have demonstrated the feasibility of high penetrations of VRES generators in the regional or nationwide US electric system [11e14], these have only evaluated one individual US region and/or have only considered a small set of hours for their analysis. This paper is based on data for the entire contiguous US of unprecedented temporal length and spatial resolution. Relying on 32 years of weather data with hourly time resolution and a spatial resolution of 40 40 km2, potential future wind and solar PV generation time series are calculated and compared to historical load profiles for the entire contiguous US, divided into the 10 FERC (Federal Energy Regulatory Commission) regions (see Fig. 1).
Similar studies concerning single European countries like Denmark  or Ireland  comprise the work of the EnergiPLAN group in Denmark. They model renewable energy systems in more detail, but with a smaller weather data basis and without transmission. On the other hand, Refs. [17, 18] investigate a renewable European future with a special focus on transmission grid extensions. Further work has been performed by some of us previously for Europe, [19e23], starting from detailed weather data and deriving general features of the electricity system. An analysis of the Australian power system, focusing attention on economics in a carbon-constrained world, can be found in Refs. [24, 25].
We present two example applications of the obtained generation data: First, it is examined how the mix of wind and solar power can be tuned to reduce the usage of back-up power plants and storage, and second, different transmission grid extensions and their effects are investigated. Both issues are first addressed on a purely technical level, where our only concern is the reduction of back-up or storage energy needed, and then on an economical level, taking costs of wind and solar PV installations and of transmission lines into account. These costs are resolved on a FERC region level to account for spatial differences.
Comparisons between technically optimal systems and cost-optimal developments allow us to judge the effect of costs as well as cost uncertainties on our projections. For the mix between wind and solar PV power, we investigate different relative costs in detail and show their impact on the optimal mix. For transmission, we confine ourselves to two cost scenarios due to computational limitations, and compare them to a heuristic approach used previously.
This paper is organized as follows: Section 2 describes the input weather data set, and how wind and solar generation time series are obtained from it. Section 3 describes the load data as well as the mismatch between VRES generation and load. Sections 4 and 5 present the two applications of the generation and load data set: Calculation of the optimal mix between wind and solar PV with respect to several objectives in Section 4, and an optimal enhancement of the transmission grid for sharing VRES among the FERC regions in Section 5. Section 6 concludes the paper.
About the Stanford University Department of Civil and Environmental Engineering
“We categorize CEE into three main areas: the Built Environment, Atmosphere and Energy, and the Water Environment. Exploring the relationships between these categories informs the direction of our curriculum. Some of the intersections are depicted in the diagram on this page; others will emerge as we continue down this path.”