Siting Renewable Energy Facilities: A Spatial Analysis of Promises and Pitfalls

Recent efforts to site renewable energy projects have provoked as much, if not more, opposition than conventional energy projects. Because renewable energy resources are often located in sensitive and isolated environments, such as pristine mountain ranges or coastal waters, siting these facilities is especially difficult. Moreover, the viability of different renewable energy projects depends not only on complex economic and environmental factors, but also on the availability of supporting infrastructures, such as transmission lines. This paper examines the spatial relationships between four types of renewable energy resources – wind, solar, geothermal, and biomass – and an empirical measure of state-level transmission-line siting difficulty. Analyses explore the locations of renewable resource potential relative to areas of high siting difficulty, state electricity demand and imports, and states with renewable portfolio standards (RPSs). Major results reveal that state resource potential varies, and siting is significantly more difficult in states that import electricity and those with RPSs. These results suggest that states with the greatest incentives to develop renewable energy also face the most serious obstacles to siting new facilities.siting, renewable energy, transmission lines, wind, solar, geothermal, biomass, geographic information systems (GIS), renewable portfolio standards (RPS)

Reductions of Galois representations for slopes in (1,2)(1,2)

We describe the semi-simplification of the mod $p$ reduction of certain crystalline two dimensional local Galois representations of slopes in the interval $(1,2)$ and all weights. The proof uses the mod $p$ Local Langlands Correspondence for $GL_2(Q_p)$. We also give a complete description of the submodules generated by the second highest monomial in the mod $p$ symmetric power representations of $GL_2(F_p)$.Comment: 41 page

Statistical Significance of spectral lag transition in GRB 160625B

Recently Wei et al (arXiv:1612.09425) have found evidence for a transition from positive time lags to negative time lags in the spectral lag data of GRB 160625B. They have fit these observed lags to a sum of two components: an assumed functional form for intrinsic time lag due to astrophysical mechanisms and an energy-dependent speed of light due to quadratic and linear Loren tz invariance violation (LIV) models. Here, we examine the statistical significance of the evidence for a transition to nega tive time lags. Such a transition, even if present in GRB 160625B, cannot be due to an energy dependent speed of light as th is would contradict previous limits by some 3-4 orders of magnitude, and must therefore be of intrinsic astrophysical origin . We use three different model comparison techniques: a frequentist test and two information based criteria (AIC and BIC). From the frequentist model comparison test, we find that the evidence for transition in the spectral lag data is favored at $3.05\sigma$ and $3.74\sigma$ for the linear and quadratic models respectively. We find that $\Delta$AIC and $\Delta$BIC have values $\gtrsim$ 10 for the spectral lag transition that was motivated as being due to quadratic Lorentz invariance vio lating model pointing to "decisive evidence". We note however that none of the three models (including the model of intr insic astrophysical emission) provide a good fit to the data.Comment: 6 pages, 1 figur

Exploring High Dimensional Free Energy Landscapes: Temperature Accelerated Sliced Sampling

Biased sampling of collective variables is widely used to accelerate rare events in molecular simulations and to explore free energy surfaces. However, computational efficiency of these methods decreases with increasing number of collective variables, which severely limits the predictive power of the enhanced sampling approaches. Here we propose a method called Temperature Accelerated Sliced Sampling (TASS) that combines temperature accelerated molecular dynamics with umbrella sampling and metadynamics to sample the collective variable space in an efficient manner. The presented method can sample a large number of collective variables and is advantageous for controlled exploration of broad and unbound free energy basins. TASS is also shown to achieve quick free energy convergence and is practically usable with ab initio molecular dynamics techniques