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.

Sustainable urban planning: parameters to the operational process

In modern society, energy consumption and respect for the environment have become essential aspects of urban planning. The rising demand for alternative sources of energy, coupled with the decline in the construction sector and material usage, gives the idea that the thinking on modern cities, where attention is given to reduced energy consumption, savings, waste recycling and respect for the surrounding environment, is being put into practice. If we examine development of the city over recent centuries, by means of the theories of the most famous and influential urban planners, it is possible to identify the major problems caused by this type of planning. For this reason, in recent urban planning the use of systems of indicators that evaluate and certify land environmentally and energetically guides the master plan toward a more efficient city model. In addition the indicators are targeted on key factors determined by the commissioner or the opportunities the territory itself provides. Due the complexity of the environmental mechanics, the process of design and urban planning has become a challenging issue. The introduction of the indicators system has made it possible to register the life of the process, with a spiral route that allows the design itself to be refined. The aim of this study, built around the creation of a system of urban sustainability indicators that will evaluate highly eco-friendly cities, is to develop a certification system for cities or portions of them. The system will be upgradeable and objective, will employ real data and will be concerned with energy production and consumption.

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.