Accurate forecasting of solar power generation with fine temporal and spatial resolution is vital for the operation grid. However, state-of-the-art approaches that combine machine learning numerical weather predictions (NWP) have coarse resolution. In this paper, we take a graph signal processing perspective model multi-site photovoltaic (PV) production time series as signals on to capture their spatio-temporal dependencies achieve higher forecasts. We present two novel neural network models...

Accurate forecasting of photovoltaic (PV) and wind production is crucial for the integration more renewable energy sources into power grid. To address limited resolution costs methods based on numerical weather predictions (NWP), we take PV data as main input forecasting. Since affected by cloud dynamics, model spatio-temporal correlations between representing systems nodes a dynamic graph embedding data, geographical information clear-sky irradiance signals that graph. We introduce new...

Plasma-enhanced low temperature growth (<300 °C) of silicon nanowires (SiNWs) and hierarchical structures via a vapor–liquid–solid (VLS) mechanism are investigated. The SiNWs were grown using tin indium as catalysts prepared by in situ H2 plasma reduction SnO2 ITO substrates, respectively. Effective at temperatures 240 °C have been achieved, while is found to be more ideal than achieving better size density control the SiNWs. Ultra-thin (4–8 nm) silica nanowires, sprouting from dendritic...

We report an in-plane solid-liquid-solid (IPSLS) mode for obtaining self-avoiding lateral silicon nanowires (SiNW) in a reacting-gas-free annealing process, where the growth of SiNWs is guided by liquid indium drops that transform surrounding $a\mathrm{\text{\ensuremath{-}}}\mathrm{Si}\ensuremath{\mathbin:}\mathrm{H}$ matrix into crystalline SiNWs. The can be $\ensuremath{\sim}\mathrm{mm}$ long, with smallest diameter down to $\ensuremath{\sim}22\text{ }\text{ }\mathrm{nm}$. A high rate...

In situ generation of indium catalyst droplets and subsequent growth crystalline silicon nanowires on ITO by plasma-enhanced CVD are reported, the wurtzite (Si–IV) phase is clearly evidenced in some wires.

We here propose an all-in situ method for growing vapor–liquid–solid (VLS) silicon nanowires (SiNWs) directly on SnO2 substrates in a plasma-enhanced chemical vapor deposition system. The tin catalysts are formed by well-controlled H2 plasma treatment of the layer. lowest temperature tin-catalyzed VLS SiNWs growth silane is ∼250 °C. effects substrate and dilution morphology compositional evolution were systematically investigated. catalyst content can be effectively controlled temperature....

Hybrid concepts based on a nanoscale combination of organic and inorganic semiconductors are promising way to enhance the cost efficiency solar cells through better use spectrum, higher aspect ratio interface, good processability polymers. A new type has been investigated. It is heterojunction between regio-regular poly(3-hexylthiophene) as an electron donor silicon acceptor. In first step towards nano-structured devices, made flat thin films these materials have studied model case...

The photovoltaics industry is adopting bifacial systems which offer improved energy harvesting compared to monofacial ones. This stems from the collection of light reflected by surroundings on rear side modules, leading system-level gains typically ranging 5% 25%rel. question arises, however, whether this gain also applies two-terminal (2T) tandem solar cells, since series-connected subcells must generate equivalent currents achieve an optimal performance. Using comprehensive simulations...

Smart grids offer an indisputable business opportunity for system operators and energy traders to engage in demand response programs. Hereby these actors may profit from trading flexibility provided at the prosumer side on markets. This paper discusses design challenges information communication technology infrastructure facilitating DR residential prosumers. It presents SEMIAH framework providing a scalable built component-based architecture with virtual power plant hearth of system. The...

Accurate forecasting of solar power generation with fine temporal and spatial resolution is vital for the operation grid. However, state-of-the-art approaches that combine machine learning numerical weather predictions (NWP) have coarse resolution. In this paper, we take a graph signal processing perspective model multi-site photovoltaic (PV) production time series as signals on to capture their spatio-temporal dependencies achieve higher forecasts. We present two novel neural network models...

Abstract Diazonium salts coupled with vinylic monomers were able to functionalize carpets of carbon nanotubes by electro‐activation in aqueous media. Hence, nano‐sized surfaces shown react active radical species solution through a new covalent grafting process called Surface Electroinitiated Emulsion Polymerization (SEEP), where diazonium are used both initiate the polymerization and form primer grafted polyphenylene‐like layer on surface. SEM TEM analyses revealed that ultrathin polymer...

Power consumption in buildings show non-linear behaviors that linear models cannot capture whereas recurrent neural networks (RNNs) can. This ability makes RNNs attractive alternatives for the model-predictive control (MPC) of buildings. However RNN lack mathematical regularity which their use challenging optimization problems. work therefore systematically investigates whether using building provides net gains an MPC framework. It compares representation power and performance two...

Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In this paper we introduce computing methods multi-site PV forecasting, which exploit the intuition that provide a dense network simple stations. These rely...

We present a three-step method to perform system identification and optimal control of non-linear systems. Our approach is mainly data driven does not require active excitation the identification. In particular, it designed for systems which only historical under closed-loop are available where commands exhibit low variability. first step, simple simulation models built run various conditions. second neural network architecture extensively trained on outputs learn physics, retrained with...

Abstract The formation of gold islands on a transparent conductive oxide by annealing thin evaporated layer is studied SEM. droplets metal formed this way may catalyze the growth nanowires or nanotubes to be used in opto‐electronic devices. effect initial thickness (between 1 nm and 4 nm) temperature 70 °C 650 °C) investigated. A qualitative description evolution given quantitative data are obtained automated image analysis. Number density, area effective diameter aggregates depend heavily...

With the rising popularity of photovoltaic (PV) power, utility companies are experiencing a growing number interconnection requests on their networks. Combined with power quality issues, distribution system operator (DSO) must go through strenuous impact studies before proceeding to installation PV systems. To address this issue, work proposes tool rapidly and accurately compute total hosting capacity (PVHC) network. Moreover, proposed allows implementation user-defined control strategies in...

Renewable energy sources (RES) are changing the operating conditions of power systems. In this context, battery storage systems (BESSs) could be a viable technical solution to maximize local consumption RES generation or provide ancillary services grid. However, lack information about real field performance is affecting diffusion BESS on market. Here we present technological comparison between different lithium-based technologies in terms density, density and efficiency based IEC 62660-1...

The emergence of bifacial photovoltaics as a serious option for large-scale power generation makes the accuracy in-situ estimation ground surface albedo increasingly critical. Recent studies have evaluated performance different models but an investigation how these should be calibrated is missing. This paper proposes geographically generalised parametrisations time-variant vegetated and desert surfaces based on worldwide database reports their compared to site-specific, unbiased...

The high-penetration of Distributed Energy Resources (DER) in low voltage distribution grids, mainly photovoltaics (PV), might lead to overvoltage the point common coupling, thus, limiting entrance renewable sources fulfill requirements from network operator. Volt-var is a control function for DER power converters that used enhance stability and reliability system. In this study, centralized algorithm provides local volt-var parameters each PV inverter, which are based on electrical grid...

Buildings are a promising source of flexibility for the application demand response. In this work, we introduce novel battery model formulation to capture state evolution single building. Being fully data-driven, identification requires one dataset from period nominal controller operation, and with relative requests, without making any assumptions on underlying, but fixed, structure. We consider parameter uncertainty in show how use risk measures encode preferences user robust sets. Finally,...