The penetration of renewable energies has increased during the last decades since it has become an effective solution to the world’s energy challenges. Among all renewable energy sources, photovoltaic (PV) technology is the most immediate way to convert solar radiation into electricity. Nevertheless, PV power output is affected by several factors, such as location, clouds, etc. As PV plants proliferate and represent significant contributors to grid electricity production, it becomes increasingly important to manage their inherent alterability. Therefore, solar PV forecasting is a pivotal factor to support reliable and cost-effective grid operation and control. In this paper, a stacked long short-term memory network, which is a significant component of the deep recurrent neural network, is considered for the prediction of PV power output for 1.5 h ahead. Historical data of PV power output from a PV plant in Nicosia, Cyprus, were used as input to the forecasting model. Once the model was defined and trained, the model performance was assessed qualitative (by graphical tools) and quantitative (by calculating the Root Mean Square Error (RMSE) and by applying the k-fold cross-validation method). The results showed that our model can predict well, since the RMSE gives a value of 0.11368, whereas when applying the k-fold cross-validation, the mean of the resulting RMSE values is 0.09394 with a standard deviation 0.01616.

The purpose of this paper is to investigate the effect of Energy Performance Certificates (EPCs) on the renovation of buildings. Thus, through the European project ENERFUND, 2 online web-based surveys were conducted in 12 countries of the European Union. It was shown that the results varied significantly both between countries and age groups and, that, on average, EPCs did play a role both in renovation decisions and whether to rent/buy a certain flat. In addition, this paper presents major key drivers and parameters related to energy renovation investment mobilisation and suggests actions that can contribute to the promotion of investments for deep energy renovation of buildings. Furthermore, it highlights potential benefits and effectiveness of using retrofitting online tools, such as the ENERFUND tool, pinpoints market failures in the building sector and provides suggestions on increasing the deep energy renovation market in Europe.

Biodiversity is a key resource as it provides both goods and services to society. However, humans value these resources differently, especially when biodiversity is exploited for its economic potential; a destruction on a scale rarely seen before. In order to decrease the threats that biodiversity is facing due to human activity, globally (climate change) and locally (economic development), individuals must have fundamental knowledge and exhibit appropriate behaviour towards biodiversity and its values. Nevertheless, the effect of human's knowledge, policies and attitudes towards biodiversity's protection are often limited by insufficient education and public support. A balance between the use of resources and technology, reconciling economic development and the need to maintain biodiversity is a challenge. The current paper looks into the knowledge level, attitudes and behaviour of university students of the Department of Environmental Science and Technology at the Cyprus University of Technology towards biodiversity. The investigation was carried out using a closed format questionnaire on a sample of first- and second-year university students (n = 44), in order to access their perceptions and attitudes towards environmental issues regarding biodiversity. The questionnaire was derived from relevant literature. The test results showed that there are significant differences with regard to the level of knowledge about biodiversity between the two groups. However, no significant differences were found on attitudes and behaviour towards biodiversity. The results have also shown that all students have a positive attitude towards biodiversity, while on the other hand, they find themselves, most of the time, unwilling to engage in environmental behaviour.