Multi-time-horizon Solar Forecasting Using Recurrent Neural Network

The non-stationarity characteristic of the solar power renders traditional point forecasting methods to be less useful due to large prediction errors. This results in increased uncertainties in the grid operation, thereby negatively affecting the reliability and increased cost of operation. This research paper proposes a unified architecture for multi-time-horizon predictions for short and long-term solar forecasting using Recurrent Neural Networks (RNN). The paper describes an end-to-end pipeline to implement the architecture along with the methods to test and validate the performance of the prediction model. The results demonstrate that the proposed method based on the unified architecture is effective for multi-horizon solar forecasting and achieves a lower root-mean-squared prediction error compared to the previous best-performing methods which use one model for each time-horizon. The proposed method enables multi-horizon forecasts with real-time inputs, which have a high potential for practical applications in the evolving smart grid.Comment: Accepted at: IEEE Energy Conversion Congress and Exposition (ECCE 2018), 7 pages, 5 figures, code available: sakshi-mishra.github.i

A novel interplanetary communications relay

A case study of a potential Earth-Mars interplanetary communications relay, designed to ensure continuous communications, is detailed. The relay makes use of orbits based on artificial equilibrium points via the application of continuous low thrust, which allows a spacecraft to hover above the orbital plane of Mars and thus ensure communications when the planet is occulted with respect to the Earth. The artificial equilibria of two different low-thrust propulsion technologies are considered: solar electric propulsion, and a solar sail/solar electric propulsion hybrid. In the latter case it is shown that the combination of sail and solar electric propulsion may prove advantageous, but only under specific circumstances of the relay architecture suggested. The study takes into account factors such as the spacecraft's power requirements and communications band utilized to determine the mission and system architecture. A detailed contingency analysis is considered for recovering the relay after increasing periods of spacecraft motor failure, and combined with a consideration for how best to deploy the relay spacecraft to maximise propellant reserves and mission duration

An Integrated Multi-Time-Scale Modeling for Solar Irradiance Forecasting Using Deep Learning

For short-term solar irradiance forecasting, the traditional point forecasting methods are rendered less useful due to the non-stationary characteristic of solar power. The amount of operating reserves required to maintain reliable operation of the electric grid rises due to the variability of solar energy. The higher the uncertainty in the generation, the greater the operating-reserve requirements, which translates to an increased cost of operation. In this research work, we propose a unified architecture for multi-time-scale predictions for intra-day solar irradiance forecasting using recurrent neural networks (RNN) and long-short-term memory networks (LSTMs). This paper also lays out a framework for extending this modeling approach to intra-hour forecasting horizons thus, making it a multi-time-horizon forecasting approach, capable of predicting intra-hour as well as intra-day solar irradiance. We develop an end-to-end pipeline to effectuate the proposed architecture. The performance of the prediction model is tested and validated by the methodical implementation. The robustness of the approach is demonstrated with case studies conducted for geographically scattered sites across the United States. The predictions demonstrate that our proposed unified architecture-based approach is effective for multi-time-scale solar forecasts and achieves a lower root-mean-square prediction error when benchmarked against the best-performing methods documented in the literature that use separate models for each time-scale during the day. Our proposed method results in a 71.5% reduction in the mean RMSE averaged across all the test sites compared to the ML-based best-performing method reported in the literature. Additionally, the proposed method enables multi-time-horizon forecasts with real-time inputs, which have a significant potential for practical industry applications in the evolving grid.Comment: 19 pages, 12 figures, 3 tables, under review for journal submissio

LunaNet: a Flexible and Extensible Lunar Exploration Communications and Navigation Infrastructure

NASA has set the ambitious goal of establishing a sustainable human presence on the Moon. Diverse commercial and international partners are engaged in this effort to catalyze scientific discovery, lunar resource utilization and economic development on both the Earth and at the Moon. Lunar development will serve as a critical proving ground for deeper exploration into the solar system. Space communications and navigation infrastructure will play an integral part in realizing this goal. This paper provides a high-level description of an extensible and scalable lunar communications and navigation architecture, known as LunaNet. LunaNet is a services network to enable lunar operations. Three LunaNet service types are defined: networking services, position, navigation and timing services, and science utilization services. The LunaNet architecture encompasses a wide variety of topology implementations, including surface and orbiting provider nodes. In this paper several systems engineering considerations within the service architecture are highlighted. Additionally, several alternative LunaNet instantiations are presented. Extensibility of the LunaNet architecture to the solar system internet is discussed

Solar Architecture: Designing Buildings to Use Solar Energy for Heating, Cooling, and Lighting

Key facts: - Simple architectural modifications allow residential and commercial buildings to use solar energy directly for heating, cooling, and lighting. - By designing buildings to match local conditions, solar energy can be harnessed anywhere in the world, even in cold, northern climates

Impurity-to-efficiency simulator: Predictive simulation of solar cell efficiencies based on measured metal distribution and cell processing conditions

We present a fast and simple 1D simulation tool to predict solar cell performance as a function of the initial iron content and distribution in the as-grown silicon wafer, the time-temperature profiles applied during the fabrication process, and several parameters related to cell architecture. The applied model consists of three parts that are validated by comparison to experimental results from literature. Assuming a time-temperature profile of a standard solar cell fabrication process, we calculate the redistribution of iron and the evolution of minority carrier lifetime for different as-grown Fe distributions. The solar cell performance as a function of the total iron concentration and the final lifetime distribution is also simulated and compared to experimental results for multicrystalline Si. Keywords: simulation, crystalline silicon solar cell, getterin

Large Integrated Absorption Enhancement in Plasmonic Solar Cells by Combining Metallic Gratings and Antireflection Coatings

We describe an ultrathin solar cell architecture that combines the benefits of both plasmonic photovoltaics and traditional antireflection coatings. Spatially resolved electron generation rates are used to determine the total integrated current improvement under AM1.5G solar illumination, which can reach a factor of 1.8. The frequency-dependent absorption is found to strongly correlate with the occupation of optical modes within the structure, and the improved absorption is mainly attributed to improved coupling to guided modes rather than localized resonant modes