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Abstract The present paper examines the phenomenon of energy poverty in Greece. Specifically, energy poverty concerns a growing number of households that have limited access to energy or are unable to pay for this energy, mainly due to insufficient thermal insulation, low income and high energy costs. The continuing economic crisis in Greece has increased the rate of energy poverty as incomes have fallen, the price of oil and PPC tariffs have risen, more households are asked to pay more than 20% of their energy bill income. Excessive energy poverty in turn has an impact on the environment (illegal logging, smog, etc.), but also to the physical and mental health of people exposed to it. The paper includes a case study which provides information and data collected from a sample of 384 households using the questionnaire method in four areas of northern Greece, which is the Edessa area in Central Macedonia, the area of Drama in Eastern Macedonia, the area of Xanthi and the Municipality of Myki (Pomakohoria) in Thrace. Initially, personal data, housing characteristics and household health status are presented. The types of heating system of the examined households and the extent to which they meet the required levels of thermal comfort are presented below. In addition, the aforementioned data is associated with the energy accounts. The findings, show that energy poverty has affected a significant proportion of households in Greece. This is due to the fact that there are households that do not meet the energy needs of their home.

Production of biodiesel from yellow grease (waste cooking oil and waste animal fats) is fast emerging as a promising alternative to address the twin challenges before the biodiesel industry today-fluctuation in prices of vegetable oil and the food versus fuel debate. Yellow grease has a high percentage of free fatty acids (FFA) and proves to be an unsuitable feedstock for biodiesel production from commercially viable alkali-catalyzed production systems due to saponification problems.“Green” methodologies based on heterogeneous solid acid catalyzed reactions have the potential to simultaneously promote esterification and transesterification reactions of yellow grease to produce biodiesel without soap formation and offer easy catalyst separation without generation of toxic streams. This paper presents kinetic studies for the conversion of model yellow grease feeds to biodiesel using a heteropolyacid supported on alumina (HSiW/Al2O3) using a batch autoclave. Three model yellow grease feeds were prepared using canola oil with added FFA such as palmitic, oleic and linoleic acid. A pseudo homogeneous kinetic model for the parallel esterification and transesterification was developed. The rate constants and activation parameters for esterification and transesterification reactions for the model yellow grease feeds were determined. The rate constants for esterification are higher than the transesterification rate constants. The kinetic model was validated using the experimental biodiesel data obtained from processing a commercial yellow grease feed. The kinetic model could be used to design novel processes to convert various low-value waste oils, fats and non-food grade oils to sustainable biodiesel. Keywords: Yellow grease, Canola oil, Free fatty acids, Heteropolyacid, Kinetics for esterification and transesterification

The benefits of aluminum lamination in improving the physical and mechanical properties of wood-based composites is now well documented. This paper shows the contribution of life cycle assessment (LCA) as a tool to assess and compare the environmental footprint in the development of laminated panels. SimaPro 9.0 software, using Ecoinvent database was used to analyze the environmental impacts associated with the manufacturing of wood aluminum-laminated (WAL) panels and aluminum honeycomb panel (AHP). The impact 2002+ method was used to estimate environmental impacts. The LCA results show that the WAL panels manufacturing had a lower environmental impact than AHP manufacturing. In term of product, wood-based composites were the best choice as a core in laminated panel manufacturing. Wood-based composite manufacturing showed environmental advantages in all damage categories except in ecosystem quality. Aluminum alloy sheets manufacturing played an important role in the generation of environmental impacts for laminated panel development.

Nowadays, the imperative need for the reduction of Greenhouse Gas (GHG) emissions leads to the wider adoption of environmentally friendly transportation means. As a result, various policies underpinning the Electric Vehicle (EV) deployment are legislated globally, and several technical advances contributing to the electrification of the transportation sector are pursued. In this paper, a comprehensive overview of the current status of the infrastructure utilized for the realization of both conductive and contactless (wireless) charging of an EV battery is conducted. Furthermore, the issue of EV integration in conventional distribution networks, as well as in future power system architectures, is discussed in detail. Particular focus is given to wireless (i.e., inductive) charging. A detailed presentation of the respective standards and charging levels, as well as the magnetic couplers and the compensation network configurations, is carried out. Moreover, innovative concepts such as dynamic and quasi-dynamic wireless charging, as well as future challenges and opportunities, are presented and discussed. Finally, smart control and communication techniques applicable to EV charging are presented in the context of the future Internet of Energy (IoE) concept.

This article proposes an effective evolutionary hybrid optimization method for identifying unknown parameters in photovoltaic (PV) models based on the northern goshawk optimization algorithm (NGO) and pattern search (PS). The chaotic sequence is used to improve the exploration capability of the NGO algorithm technique while evading premature convergence. The suggested hybrid algorithm, chaotic northern goshawk, and pattern search (CNGPS), takes advantage of the chaotic NGO algorithm’s effective global search capability as well as the pattern search method’s powerful local search capability. The effectiveness of the recommended CNGPS algorithm is verified through the use of mathematical test functions, and its results are contrasted with those of a conventional NGO and other effective optimization methods. The CNGPS is then used to extract the PV parameters, and the parameter identification is defined as an objective function to be minimized based on the difference between the estimated and experimental data. The usefulness of the CNGPS for extraction parameters is evaluated using three distinct PV models: SDM, DDM, and TDM. The numerical investigates illustrate that the new algorithm may produce better optimum solutions and outperform previous approaches in the literature. The simulation results display that the novel optimization method achieves the lowest root mean square error and obtains better optima than existing methods in various solar cells.

A vehicle model is used to evaluate a novel powertrain that is comprised of a dual energy storage system (Dual ESS). The system includes two battery packs with different chemistries and the necessary electronic controls to facilitate their coordination and optimization. Here, a lithium-ion battery pack is used as the primary pack and a Zinc-air battery as the secondary or range-extending pack. Zinc-air batteries are usually considered unsuitable for use in vehicles due to their poor cycle life, but the model demonstrates the feasibility of this technology with an appropriate control strategy, with limited cycling of the range extender pack. The battery pack sizes and the battery control strategy are configured to optimize range, cost and longevity. In simulation the vehicle performance compares favourably to a similar vehicle with a single energy storage system (Single ESS) powertrain, travelling up to 75 km further under test conditions. The simulation demonstrates that the Zinc-air battery pack need only cycle 100 times to enjoy a ten-year lifespan. The Zinc-air battery model is based on leading Zinc-air battery research from literature, with some assumptions regarding achievable improvements. Having such a model clarifies the performance requirements of Zinc-air cells and improves the research community's ability to set performance targets for Zinc-air cells.

Hydrogen, as a maritime fuel, is one of the solutions that will assist the shipping sector in addressing the challenges regarding decarbonization, taking into consideration the targets set for 2030 and 2050. The extensive utilization of hydrogen requires massive production of green hydrogen and the development of proper infrastructure to support a sustainable supply chain. An alternative solution is based on the on-board production of hydrogen, where production units are installed on-board the vessel. Along these lines, the HYMAR project aims to test the utilization of a hydrogen production unit for on-board use. The article deals with the use of hydrogen as a fuel for internal combustion engines, taking into consideration reports from literature and the preliminary results of the HYMAR project, focusing on the environmental impact and the reduction in emissions. Experimental investigation on a marine auxiliary engine for power generation, under the HYMAR project, leads to promising results regarding the environmental footprint of the internal combustion engine when hydrogen is added in the fuel mix with increasing percentages.

These data sets provide the WRF [1] calculated wind data for Pritzwalk (onshore) and FINO3 (offshore) as Python dictionaries. Additionally, the files contain k-means cluster objects derived from these profiles. These data sets were used for power assessment and design exploration of Airborne Wind Energy Systems using the awebox [2] optimization toolbox. WRF setups are described in detail and used in publication [3,4,5]. Wind data are interpolated to fixed heights of: [10, 28, 50, 70, 90, 100, 150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 700, 800, 1000, 1200] meters above ground. Onshore wind data: Location lat: 53° 10.78' N; long: 12° 11.35' E Time: 1 September 2015 - 31 August 2016 Timestep: 10 min Offshore wind data: Location lat: 55° 11.7' N, long: 7° 9.5' E Time: 1 September 2013 - 31 August 2014 Timestep: 10 min The clusters are derived from both horizontal wind velocity components using the scikit-learn’s k-means clustering algorithm [6]. For our purposes, wind vectors were rotated such that the main wind speed always points in the same direction (u_main,u_deviation). [1]: Weather Research and Forecasting Model [2]: awebox [3]: Improving mesoscale wind speed forecasts using lidar-based observation nudging for airborne wind energy systems [4]: Offshore and onshore ground-generation airborne wind energy power curve characterization [5]:Ground-generation airborne wind energy design space exploration [6]: sklearn.cluster.KMeans