• Energy Research
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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.

In order to achieve paramount economy, hybrid renewable energy sources are gaining importance, as renewable sources are costless. Over the past few years wind energy incorporation drew more consideration in the electricity market, as wind power took an affirmative role in energy saving as well as sinking emission pollutants. Recently developed Grey wolf optimizer (GWO) algorithm has conspicuous behavior for verdicting global optima, without getting ensnared in premature convergence. In the proposed research the exploitation phase of the grey wolf optimizer has been further improved using random exploratory search algorithm, which uses perturbed solutions vectors along with previously generated solution vectors. The paper presents a hybrid version of Grey Wolf Optimizer algorithm combined with random exploratory search algorithm (hGWO-RES) for the solution of combinatorial scheduling and dispatch problem of electric power systems. To validate the feasibility of the algorithm, the proposed algorithm has been tested on 23 benchmark problems. To verify the feasibility and efficacy of operation of proposed algorithm on generation scheduling and dispatch of electric power systems, small and medium scale power systems consisting of 7-, 10-, 19-, 20- and 40-generating units systems taken into consideration. Commitment and scheduling pattern has been evaluated with and without wind integration and it has been experimentally founded that proposed hybrid algorithm provides superior solution as compared to other recently reported meta-heuristics search algorithms.

This paper evaluated the environmental effects of socially responsible investments (SRIs) in European countries and analyzed the differentiation between them in terms of SRIs and selected features in the environmental dimension. The first section of the paper discusses contemporary trends in Europe and in certain European countries, whilst the second compares SR environmental investments and environmental factors in selected European countries from a multidimensional perspective. The aim of the study was to identify and evaluate these trends as well as to find similarities and differences between European countries, and subsequently to indicate groups of countries with similar approaches to pro-ecological investments. In order to solve the problem, descriptive and multidimensional statistical methods were used, namely correspondence analysis (CA). Although the research results clearly revealed upward tendencies in the volume of SR environmental investments in the analyzed period, they nonetheless represent a relatively low share in the total number of socially responsible investments. The overall growth in SRIs in Europe may have resulted from the more intense activities of policymakers in some countries as a consequence of concluding agreements reached during the 21st Conference of the Parties (COP21) in 2015. The results of the study also revealed no significant correlations between SR environmental investments and environmental variables among the European countries analyzed; hence, there is no substantial evidence that investors’ assets contribute to the improvement of the environment.

Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

Wind characteristics (e.g., mean wind speed, gust factor, turbulence intensity and integral scale, etc.) are quite scattered in different measurement conditions, especially during typhoon and/or hurricane processes, which results in the structural engineer ambiguously determining the wind parameters in wind-resistant design of buildings and structures in cyclone-prone regions. In tropical cyclones (including typhoons and hurricanes), the inconsistent wind characteristics may be in part ascribed to the complex flow structure with the coexistence of both mechanical and convective turbulence in the boundary layer of tropical cyclones. Another significant contribution to the scattered wind characteristics is due to various measurement conditions (e.g., terrain exposure and height) and data processing schemes (e.g., averaging time). The removal of the inconsistency in the field-measurement system may offer a more rational comparison of measured wind data from various observation platforms, and hence facilitates a better identification scheme of the wind characteristics to guide the urban planning design and wind-resistant design of buildings and structures. In this study, an analytical framework was firstly proposed to eliminate the potential observation-related effects in wind characteristics and then the wind characteristics of seven field measured tropical cyclones (four typhoons and three hurricanes) were comparatively investigated. Specifically, field measurements of wind characteristics were converted to a standard reference station with a roughness length of 0.03 m, observation duration of 10 min for mean wind and averaging time of 3 s for gusty wind at a 10 m height. The differences of the measured wind characteristics between the typhoons and hurricanes were highlighted. The standardized turbulent wind characteristics under the analytical framework for typhoons and hurricanes were compared with the corresponding recommendations in standard of American Society of Civil Engineers (ASCE 7-10) and Architectural Institute of Japan Recommendations for Loads on Buildings (AIJ-RLB-2004).

Background: The global palm oil market experienced a remarkable boom since the year 2000. Since palm oil can be used for biodiesel production, the global expansion of oil palm cultivation has been associated with the global biofuel boom. Biofuel policies—especially those adopted in the European Union (EU)—have been blamed for the socio-environmental impacts of oil palm expansion. We explore how the global biofuel boom interacts with national geographies and social-economic and political processes to produce country-specific trajectories of biofuel crops expansion. We analyse the expansion of oil palm cultivation in Colombia between 2000 and 2010 from a political ecology perspective. Methods: The analysis is based on a framework that positions expansion of commodity frontiers within the ‘space-of-flows’ and the ‘space-of-place’. Through this approach, we identify the markets and geographies that define the country-specific trajectories of expansion of oil palm in Colombia, and their connections with general patterns of land control. The empirical analysis is based on primary data collected during fieldwork, and on an extensive review of secondary data about the palm oil sector and the socio-environmental effects of oil palm expansion in the country. Results: The contemporary oil palm expansion in Colombia was not specifically influenced by the international biofuel market. Expansion was characterized by an increasing production of palm oil for biodiesel, to supply a policy-driven national biofuel market controlled by national palm oil producers. The evidence shows that this oil palm expansion proceeded through a variety of land control practices that constitute forms of ‘accumulation by dispossession’ and ‘assimilation’. These are embedded in contextual factors that include the agrarian history of Colombia, the armed conflict, and government policies. Conclusions: Our study shows that the ways in which expansion of biofuel crops unfold in each producing country depend not only on the global biofuel market. They are also shaped by the country-specific geographies and political economies. Therefore, research and policies on the global expansion of energy crops should account for the complex and interrelated factors that mediate the specific ways in which the global demand for biofuels creates biofuel crop booms at country level.

Abstract Limiting the increase of global temperature requires electrification of the railway transport, which is relatively a distinct mode of transport in terms of economy, business and socialization of a country. However, battery complemented railway transport systems such as fuel cell hybrid railway propulsion systems are constrained by the high cost of the battery, and suboptimal performance of the fuel cell under varying loads. Optimized selection of battery can reduce its costs associated with sizing, life and utilization. Similarly, managing the load distribution between the battery and fuel cell can reduce the load variations concern for fuel cell. In this study, model-based selective characterization of the battery and fuel cell is done to identify the optimal features and constraints. Following characterization, the load allocation to battery and fuel cell is determined with the targets of collaborative utilization of optimal features and mitigation of constraints. Subsequently, considering this load allocation and results of characterization, conditions are proposed for reliable sizing and optimized selection of battery. The significance of the proposed conditions in reliable sizing is explored. Based on these conditions, certain commercially developed batteries are evaluated for optimized selection of battery. The results signify this study as a foundation for research on the reliable sizing and optimized selection of battery in fuel cell hybrid railway propulsion systems.

ABSTRACTThe goal of this study was to analyse the combustion characteristics and emissions of Jatropha curcas biodiesel (JCB) when run in a diesel engine. Jatropha curcas oil was used to produce Jatropha curcas biodiesel (JCB) through a transesterification process. The major fuel properties of JCB, including the acid value, kinematic viscosity, flash point, gross heating value, and iodine value, were determined and compared with that of soybean biodiesel (SBM), sunflower seed biodiesel (SFM), mackerel fish oil biodiesel (MB), and premium diesel (D). JCB had a higher density, acid value, kinematic viscosity, iodine value and flash point, but a lower gross heating value, than D. JCB was then used to analyze combustion characteristics, CO, CO2, NO, NOx, SO2, and particulate matter (PM), under varied engine speeds and varied engine loads. The experimental results show CO2 concentration increased with increasing engine loads for all fuels. Engine trials on D exhibited better combustion efficiency at lower engine loads (0 kW–4 kW) but engine trials on JCB exhibited better combustion efficiency for higher engine loads (5 kW– 8 kW). JCB emitted more NO and NOx on a loaded engine. Engine trials on JCB emitted higher PM concentration when the engine was not loaded, while engine trials on MB produced higher PM concentration when the engine was loaded. The estimated CO2 emissions for JCB, MB, and D are 9221.3, 9617.2, and 10185.0 g (gal fuel)–1, respectively.