Hybrid and Intelligent Energy Storage Systems in Standalone Photovoltaic Applications.

Remote systems such as communication relays or irrigation control installations cannot usually be powered by the electrical grid. One of the alternatives is to power these systems through solar panels, in what is known as standalone photovoltaic applications.Most of these systems need a continuous operation, but a standalone photovoltaic installation cannot be powered during the night. For this reason, they use batteries to store excess energy during the day. These storage systems have been traditionally based on Valve Regulated Lead Acid (VRLA) batteries, but some effects can alter their performance in terms of reliability, operation cost and maintenance. One of the key issues that alter the energy behavior of the photovoltaic off-grid systems is the Partial State of Charge (PSoC) effect: Batteries cannot be completely charged as manufacturers indicate due to the day-night cycle. This gets the battery into an intermediate state of charge that effectively reduces its capacity, even halving it in some cases. To mitigate the impact of these effects on the installation, batteries tend to be oversized with some security margins. These oversizing factors can be incredibly high and have a huge impact on the deployment and maintenance cost of the facility.The first part of this thesis highlights some of these key concepts, analyzing which of them are critical in specific design cases, modeling them into a simulation tool, and as an outcome, establishing optimal sizing regions for the installations. After the analysis, different ways of improving the performance of the installations are proposed. One idea to mitigate PSoC is to combine different storage technologies in a Hybrid Energy Storage Systems (HESS). HESSs have traditionally combined high energy density elements as batteries with high power density elements as ultracapacitors. An iteration of this idea is carried out throughout this thesis, where different types of batteries are combined. Each of them is best fitted to different power patterns in the application, such as daily cycles or emergency periods. It is possible to further increase the performance by using intelligent algorithms to improve the functionalities of the Battery Management Systems embedded in these applications. To this end, failure prediction and health estimation algorithms are proposed as contributions of this work. These new algorithms endow the HESS with tools to predict possible energy disruption events and to anticipate aging, and thus, act accordingly.<br /

The role of hydrogen and fuel cells in the global energy system

Hydrogen technologies have experienced cycles of excessive expectations followed by disillusion. Nonetheless, a growing body of evidence suggests these technologies form an attractive option for the deep decarb onisation of global energy systems, and that recent improvements in their cost and performance point towards economic viability as well. This paper is a comprehensive review of the potential role that hydrogen could play in the provision of electricity, h eat, industry, transport and energy storage in a low - carbon energy system, and an assessment of the status of hydrogen in being able to fulfil that potential. The picture that emerges is one of qualified promise: hydrogen is well established in certain nic hes such as forklift trucks, while mainstream applications are now forthcoming. Hydrogen vehicles are available commercially in several countries, and 225,000 fuel cell home heating systems have been sold. This represents a step change from the situation of only five years ago. This review shows that challenges around cost and performance remain, and considerable improvements are still required for hydrogen to become truly competitive. But such competitiveness in the medium - term future no longer seems an unrealistic prospect, which fully justifies the growing interest and policy support for these technologies around the world

Dataset for "Sequential Feature Selection for Power System Event Classification Utilizing Wide-Area PMU Data"

This dataset supports our paper 'Sequential Feature Selection for Power System Event Classification Utilizing Wide-Area PMU Data' submitted to Frontiers in Energy Researc

Consumption Profile Data

Relevant 24 hours data set for consumption profiles in a typical low voltage gri

Specific heating consumption in the residential sector of Serbia—Example of the city of Kragujevac

© 2015 Elsevier B.V. All rights reserved. In this paper, the specific consumption of the heat energy supplied by three most utilized heating systems (district heating, gas and electricity system) in the residential sector of the city of Kragujevac (Serbia) is analysed. Required data are provided by combining data from local utility companies with national census results. Comparison of present tariff systems shows that consumers in the residential buildings are the most motivated for energy savings if they use electricity or gas as energy source. The specific energy consumption in district heating system shows relatively high quantities, primarily as a consequence of dominant unmotivating tariff payment system. The average heat consumption from gas and electricity sources relatively fits to EU average, but the electricity consumption of the electric heaters is not acceptable in long term. Low electricity price in Serbia and high price of unit of energy from district heating system of the city of Kragujevac (and Serbia) will lead to an increase of electric energy consumption which will cause additional problems related to covering of that consumption from domestic energy sources

Time Series Dataset for Modeling and Forecasting of N2O in Wastewater Treatment

his dataset presents two years of high-resolution nitrous oxide (N2O) measurements for time series modeling and forecasting in wastewater treatment plants (WWTP). The dataset comprises frequent, real-time measurements from a full-scale WWTP, with a sample interval of 2 minutes, making it ideal for developing models for real-time operation and control

Satellite-based Data Collection Architecture for Virtual Power Plant Management in Rural Areas

Smart grid is envisaged to be the next-generation electrical power grids and this is founded based on successfully building up smart grid communication networks that can support all identified smart grid functionalities. Despite a range of communication choices available, utilities still struggle with how to affordably and reliably extend their networks to 100% of their service territories, especially to remote locations. In all smart grid models, it is often emphasized that consumers play a vital role in electricity management of supply and demand, and are expected to be co-producers of electricity, so-called prosumers. As such, virtual power plants (VPPs) by interconnecting hundreds of prosumers are expected to be a new paradigm shift in smart grid systems to better utilize the distributed energy sources. However, efficient VPP management is of great challenge in rural areas that are beyond the reach of primary networks while requiring enormous data exchange. To provide connectivity in rural areas, this paper proposes a satellite-based smart grid communication architecture for the efficient VPP management that requires collecting data from prosumers forming the VPP. Also, a priority-based scheduling algorithm for different smart grid data types is proposed to improve the performance of delay-sensitive applications. Simulation results demonstrate that the satellite-based communications can be a viable solution as a mean of smart grid communications for VPPs