An agent-based simulator to estimate domestic energy use

Throughout recent years, there has been an increase in the population size, as well as a fast economic growth, which has led to an increase of the energy demand that comes mainly from fossil fuels. In order to reduce the ecological footprint, governments have implemented sustainable measures and it is expected that by 2035 the energy produced from renewable energy sources, such as wind and solar would be responsible for one-third of the energy produced globally. However, since the energy produced from renewable sources is governed by the availability of the respective primary energy source there is often a mismatch between production and demand, which could be solved by adding flexibility on the demand side through demand response (DR). DR programs influence the end-user electricity usage by changing its cost along the time. Under this scenario the user needs to estimate the energy demand and on-site production in advance to plan its energy demand according to the energy price. This work focuses on the development of an agent-based electrical simulator, capable of: (a) estimating the energy demand and on-site generation with a 1-min time resolution for a 24-h period, (b) calculating the energy price for a given scenario, (c) making suggestions on how to maximize the usage of renewable energy produced on-site and to lower the electricity costs by rescheduling the use of certain appliances. The results show that this simulator allows reducing the energy bill by 11% and almost doubling the use of renewable energy produced on-site.

Context-based identification of energy consumption in industrial plants

Nowadays, reducing energy consumption is one of the highest priorities and biggest challenges faced worldwide and in particular in the industrial sector. Given the increasing trend of consumption and the current economical crisis, identifying cost reductions on the most energy-intensive sectors has become one of the main concerns among companies and researchers. Particularly in industrial environments, energy consumption is affected by several factors, namely production factors(e.g. equipments), human (e.g. operators experience), environmental (e.g. temperature), among others, which influence the way of how energy is used across the plant. Therefore, several approaches for identifying consumption causes have been suggested and discussed. However, the existing methods only provide guidelines for energy consumption and have shown difficulties in explaining certain energy consumption patterns due to the lack of structure to incorporate context influence, hence are not able to track down the causes of consumption to a process level, where optimization measures can actually take place. This dissertation proposes a new approach to tackle this issue, by on-line estimation of context-based energy consumption models, which are able to map operating context to consumption patterns. Context identification is performed by regression tree algorithms. Energy consumption estimation is achieved by means of a multi-model architecture using multiple RLS algorithms, locally estimated for each operating context. Lastly, the proposed approach is applied to a real cement plant grinding circuit. Experimental results prove the viability of the overall system, regarding both automatic context identification and energy consumption estimation.

Futures of automobile industry and challenges on sustainable development and mobility

Portugal had only very few foresight exercises on the automobile sector, and the most recent one was a survey held in a project on work organisation systems in the automobile industry, its recent historical paths and the special strategies of location of companies (the WorTiS project). This involved several teams with different disciplinary backgrounds and from two Portuguese universities. The provisional main results of the first round of a Delphi survey held in Portugal on the automotive sector were already published, but a further analysis was not yet done. This foresight survey was done under the WorTiS project, developed in 2004 by IET – Research Centre on Enterprise and Work Innovation (at FCT-UNL), and financed by the Portuguese Ministry of Science and Technology. Some of this experience on foresight analysis is also been transferred to other projects, namely the WORKS project on work organisation restructuring in the knowledge society that received the support from EC and still is running. The majority of experts considered having an average of less knowledge in almost all the scenario topics presented. This means that information on the automotive industry is not spread enough among academics or experts in related fields (regional scientists, innovation economists, engineers, sociologists). Some have a good knowledge but in very specialised fields. Others have expertise on foresight, or macroeconomics, or management sciences, but feel insecure on issues related with futures of automobile sector. Nevertheless, we considered specially the topics where the experts considered themselves to have some knowledge. There were no ���irrelevant��� topics considered as such by the expert panel. There are also no topics that are not considered a need for co-operation. The lack of technological infrastructures was not considered as a hindered factor for the accomplishment of any scenario. The experts��� panel considered no other international competence besides US, Japan or Germany in these topics. Special focus will be made in this paper on the topic 2. Public policy and automobile industries, and more specifically on the technological and/or research policies issues, where one can specify the automobile���s role in transport policies with further implications like environment, safety, energy, mobility.

Providing energy efficiency location-based strategies for buildings using linked open data

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Renewable energy systems the theme for the PACITA summer school on TA, Li��ge, Belgium, 25 28 June 2012

The summer school ���Renewable Energy Systems: Role and Use of Parliamentary Technology Assessment��� was the first European Summer School with a pure focus on technology assessment. The aim of the three-day long summer school of the European project Parliaments and Civil Society in Technology Assessment (PACITA) was to create awareness of the potential of technology groups in Europe. Therefore, the summer school involved keynotes, practical exercises, mutual reflection, cutting edge training and networking to deal with the theme of renewable energy systems out of the perspective of Technology Assessment (TA), to meet transition objectives or to critically assess energy technologies.

Project of a bandgap voltage reference and a temperature sensor for "energy harvest" systems

Disserta����o para obten����o do Grau de Mestre em Engenharia Electrot��cnica e Computadores

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Inclusion of disabled people in siemens AG'S energy management division

This work project is a business plan for a project regarding corporate social entrepreneurship that will be developed by Siemens Switchboard Factory in Corroios. The main purpose of this project is to understand the viability of a partnership between Siemens AG���s and CERCISA in order to include disabled people into Siemens AG���s Energy Management Division, with the goal of achieving social and economic impact by insources activities while complying with the law1. The produced output, a business plan, aims to study and understand the practical suitability and feasibility of the concepts and propose a sustainable project that can be replicated, starting with a pilot testing and validation period.

Historic and potential technology transition paths of grid battery storage: Co-evolution of energy grid, electric mobility and batteries

Scarcity of fuels, changes in environmental policy and in society increased the interest in generating electric energy from renewable energy sources (RES) for a sustainable energy supply in the future. The main problem of RES as solar and wind energy, which represent a main pillar of this transition, is that they cannot supply constant power output. This results inter alia in an increased demand of backup technologies as batteries to assure electricity system safety. The diffusion of energy storage technologies is highly dependent on the energy system and transport transition pathways which might lead to a replacement or reconfiguration of embedded socio-technical practices and regimes (by creating new standards or dominant designs, changing regulations, infrastructure and user patterns). The success of this technology is dependent on hardly predictable future technical advances, actor preferences, development of competing technologies and designs, diverging interests of actors, future cost efficiencies, environmental performance, the evolution of market demand and design and evolution of our society.