An Investigation of Equivalence Principle Violations Using Solar Neutrino Oscillations in a Constant Gravitational Potential

Neutrino oscillations induced by a flavor-dependent violation of the Einstein Equivalence Principle (VEP) have been recently considered as a suitable explanation of the solar electron-neutrino deficiency. Unlike the MSW oscillation mechanism, the VEP mechanism is dependent on a coupling to the local background gravitational potential $\Phi$. We investigate the differences which arise by considering three-flavor VEP neutrinos oscillating against fixed background potentials, and against the radially-dependent solar potential. This can help determine the sensitivity of the gravitationally-induced oscillations to both constancy and size (order of magnitude) of $\Phi$. In particular, we consider the potential of the local superculster, $|\Phi|=3\times 10^{-5}$, in light of recent work suggesting that the varying solar potential has no effect on the oscillations. The possibility for arbitrarily large background potentials in different cosmologies is discussed, and the effects of one such potential ($\Phi = 10^{-3}$) are considered.Comment: 12pp, LaTeX; 12 figures (bitmapped postscript); Submitted to Phys Rev

Measuring the solar potential of a city and its implications on energy policy

This research investigates the maximum potential energy that can be made available by efficiently installing PV systems on buildings throughout a city, from the central business district (CBD) out to low density suburbs. The purpose of this is to evaluate the contribution that electricity from PVs can make to reduce the electricity load of a city, supply the needs of a mixture of building types, reduce peak electricity demand and contribute towards the charging of electric vehicles (EVs). A sample of the main urban building types have been taken and reassembled into a representative typical cross-section of a city. The application of PVs for all the building types is investigated and then the potential electricity distribution is evaluated for different urban densities and dispersion patterns. This research is concerned not only with how individual buildings may gain from distributed generation (DG) but, more importantly, how a city as a whole may benefit. The results indicate that low dense suburbia is not only the most efficient collector of solar energy but that enough excess electricity can be generated to power daily transport needs of suburbia and also contribute to peak daytime electrical loads in the city centre. This challenges conventional thinking that suburbia is energy inefficient. While a compact city may be more efficient for the internal combustion engine vehicles, a dispersed city is more efficient when DG solar power is the main energy source and EVs are the means of transport

Aerosol-induced losses in the solar potential

The atmospheric aerosol loading may significantly influence the performance in solar power production. The impact can be very different both in space (even in short distance) and time (shortterm fluctuations as well as long-term trend). Aiming to ensure a high degree of generality, this study is focused on the aerosol impact on the collectable solar energy. Thus, the results are independent of solar plants characteristics. A new methodology for estimating the average daily,monthly, and yearly losses in the solar potential due to aerosols is proposed. For highlighting the loss in the overall solar potential, a new ideal scenario is defined as a reference for the atmospheric aerosol background. A new equation for computing the solar potential loss is proposed to adjust for possible biases. In a departure from similar studies, the analysis relies on ground measurements (BSRN and AERONET), always more accurate than remotely sensed satellite data. The seldom discussed impact of aerosol type is considered. As a general conclusion, the monthly and yearly reductions of the solar potential due to aerosols are estimated at 12 locations spread around the globe, amounting to losses of the solar potential ranging from 0.6% to as high as 7.2%

Setting intelligent city tiling strategies for urban shading simulations

Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements. In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500 m width and 200 m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300 m width and 100 m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations

Estimating Residential Solar Potential Using Aerial Data

Project Sunroof estimates the solar potential of residential buildings using high quality aerial data. That is, it estimates the potential solar energy (and associated financial savings) that can be captured by buildings if solar panels were to be installed on their roofs. Unfortunately its coverage is limited by the lack of high resolution digital surface map (DSM) data. We present a deep learning approach that bridges this gap by enhancing widely available low-resolution data, thereby dramatically increasing the coverage of Sunroof. We also present some ongoing efforts to potentially improve accuracy even further by replacing certain algorithmic components of the Sunroof processing pipeline with deep learning

Net solar generation potential from urban rooftops in Los Angeles

Rooftops provide accessible locations for solar energy installations. While rooftop solar arrays can offset in-building electricity needs, they may also stress electric grid operations. Here we present an analysis of net electricity generation potential from distributed rooftop solar in Los Angeles. We integrate spatial and temporal data for property-level electricity demands, rooftop solar generation potential, and grid capacity constraints to estimate the potential for solar to meet on-site demands and supply net exports to the electric grid. In the study area with 1.2 million parcels, rooftop solar could meet 7200 Gigawatt Hours (GWh) of on-site building demands (~29% of demand). Overall potential net generation is negative, meaning buildings use more electricity than they can produce. Yet, cumulative net export potential from solar to grid circuits is 16,400 GWh. Current policies that regulate solar array interconnection to the grid result in unutilized solar power output of 1700 MW. Lower-income and at-risk communities in LA have greater potential for exporting net solar generation to the grid. This potential should be recognized through investments and policy innovations. The method demonstrates the need for considering time-dependent calculations of net solar potential and offers a template for distributed renewable energy planning in cities

Three-dimensional urban solar potential maps: Case study of the i-Scope project

Solar maps as web cartographic products that provide information on solar potential of surfaces on the Earth have been exploited in decision making, awareness raising, and promoting the use of solar energy. Web based solar maps of cities have become popular services as the use of solar energy is especially attractive in urban environments. The article discusses the concept and aspects of urban solar potential maps on the example of the i-Scope project as a case study. The i-Scope roof solar potential service built on 3-D urban information models was piloted in eight European cities. To obtain precise data on solar irradiation, a good quality digital surface model is required. A cost efficient innovative method for generation of digital surface model from stereophotogrammetry for urban areas where no advanced source data (e. g. LiDAR) exist is developed. The method works for flat, shed and gable roofs and provides sufficient accuracy of digital surface model