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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.

Abstract The equation for the temperature distribution in a uranium rod under transient conditions is subjected to the finite Hankel transform, to produce a formal relationship between the physical parameters of rate of heat production, rate of heat removal and the temperature at any point in the rod. The form of solution is then applied to find the changes in uranium surface and centre temperatures following arbitrary changes in the rates of heat production and heat removal. The method is an inverse one in that arbitrary forms are assumed for a function φ(t) which is introduced into the equations, and the resulting variations of uranium temperature and rates of heat production and removal are examined. Within this limitation, however, the temperature and reactivity changes within the reactor can be determined for a short period of time following a disturbance, during which the relatively small thermal capacity of the uranium makes it the dominating variable.

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.

Abstract Energy storage systems (ESS) are widely used in active distribution networks (ADN) to smoothen the drastic fluctuation of renewable energy sources (RES). In order to enhance the scalability and flexibility of ESS, a virtual energy storage system (VESS), which is composed of battery energy storage system (BESS), RES as well as flexible loads (FL), is developed in this paper to realize the functionalities of ESS in more cost-effective way in ADN. Aiming at achieving voltage regulation, dynamic pricing strategies based on system voltage condition are designed for VESS. A distributed real-time power management model containing dynamic pricing strategies is proposed to accomplish the voltage regulation and economic power sharing in VESS. Moreover, a set of distributed algorithms, over time-varying unbalanced directed networks, are designed for dynamic pricing strategies and optimal power management model. Furthermore, the convergence property, optimality and system voltage stability are explained by detailed mathematical analysis. Three various case studies which were ran on a real time digital simulator (OPAL-RT OP5600) were designed to validate the effectiveness of the strategy. Finally, simulation results show that the economic power dispatch and voltage regulation are achieved among VESS simultaneously, even in the presence of time-varying directed and unbalanced communication networks.

The Intergovernmental Panel on Climate Change (IPCC) report that to limit warming to 1.5 °C, Bioenergy with Carbon Capture and Storage (BECCS) is required. Integrated assessment models (IAMS) predict that a land area between the size of Argentina and Australia is required for bioenergy crops, a 3–7 time increase in the current bioenergy planting area globally. The authors pose the question of whether vertical farming (VF) technology can enable BECCS deployment, either via land sparing or supply. VF involves indoor controlled environment cultivation, and can increase productivity per unit land area by 5–10 times. VF is predominantly being used to grow small, high value leafy greens with rapid growth cycles. Capital expenditure, operational expenditure, and sustainability are challenges in current VF industries, and will affect the ability to utilise this technology for other crops. The authors argue that, whilst challenging, VF could help reach wider climate goals. Application of VF for bioenergy crops could be a game changer in delivering BECCS technologies and may reduce the land footprint required as well as the subsequent associated negative environmental impacts. VF bioenergy could allow us to cultivate the future demand for bioenergy for BECCS on the same, or less, land area than is currently used globally.

In electric power generation and distribution systems, three structures are capable of impacting energy quality: generation, distribution and loads. Currently, the diversity of the latter ranges from purely resistive loads such as heating systems to extremely nonlinear loads such as switched electronic power supplies. This has dramatically affected the quality of electric energy. The operation of these loads contributes to the reduction of the power factor of the installation, the injection of harmonic currents in the electrical network and the imbalance of currents and voltages between the phases in the case of three-phase systems. The implementation of a method capable of recognizing electrical loads and identifying them through algorithms can be used to manage the electric energy consumption, contributing a lot to the improvement of the quality of electric energy. In order to deal with uncertainty in the identification of these loads, probability distributions will be applied, which are able to handle uncertainty through a probabilistic modeling using Bayesian Networks.

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.

In this paper, we study the interactions among interconnected autonomous microgrids, and propose a joint energy trading and scheduling strategy. Each interconnected microgrid not only schedules its local power supply and demand, but also trades energy with other microgrids in a distribution network. Specifically, microgrids with excessive renewable generations can trade with other microgrids in deficit of power supplies for mutual benefits. Since interconnected microgrids operate autonomously, they aim to optimize their own performance and expect to gain benefits through energy trading. We design an incentive mechanism using Nash bargaining theory to encourage proactive energy trading and fair benefit sharing. We solve the bargaining problem by decomposing it into two sequential problems on social cost minimization and trading benefit sharing, respectively. For practical implementation, we propose a decentralized solution method with minimum information exchange overhead. Numerical studies based on realistic data demonstrate that the total cost of the interconnected-microgrids operation can be reduced by up to 13.2% through energy trading, and an individual participating microgrid can achieve up to 29.4% reduction in its cost through energy trading. To appear in IEEE Transactions on Smart Grid

AbstractHeterojunction CdS/CdTe thin film solar cells were fabricated with a superstrate structure consisting of the successive layers: soda lime glass/ITO/CdS/CdTe/back contact. ZnTe:Cu films were deposited on the back surface of the CdTe layer presenting as ohmic back contact. The substrate was soda lime glass coated with ITO films by rf magnetron sputtering serving as the transparent front contact. A thin layer of CdS with thickness about 80nm was applied by chemical bath deposition. Close-spaced sublimation of the CdTe films was accomplished by placing a CdTe source in a close proximity (6mm) to the substrate in vacuum chamber with low pressure about 3×10-2 mbar. The source was heated to 550 ∘C and the substrate to 450 ∘C. This arrangement causes Cd and Te to sublime from source and diffuse to the substrate. The fabricated cells were investigated using current-voltage (I-V) in the temperature range 20-300K under a standard AM1.5 illumination in order to define the transport mechanism in the heterojunction. Tunnelling enhanced interface recombination has been found to dominate carrier transport mechanism in the junction at all investigated temperatures.